International Journal of

ADVANCED AND APPLIED SCIENCES

EISSN: 2313-3724, Print ISSN: 2313-626X

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 Volume 8, Issue 8 (August 2021), Pages: 1-8

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 Original Research Paper

 Title: Simulating fouling impact on the permeate flux in high-pressure membranes

 Author(s): Hisham A. Maddah *

 Affiliation(s):

 Department of Chemical Engineering, King Abdulaziz University, Rabigh, Saudi Arabia

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 * Corresponding Author. 

  Corresponding author's ORCID profile: https://orcid.org/0000-0002-8208-8629

 Digital Object Identifier: 

 https://doi.org/10.21833/ijaas.2021.08.001

 Abstract:

Porous high-pressure membranes have been widely used for saline water desalination. However, fouling (concentration polarization) extensively reduces permeate flux in reverse osmosis (RO) and/or nanofiltration (NF) modules. Fouling arises from pore blocking, organic adsorption, cake formation, inorganic or biological precipitation reducing water flux. Herein, we investigated the effect of feed water with various NaCl concentrations on fouling of RO and/or NF and the permeate water flux. A parabolic (or diffusion) partial differential equation (PDE) was used to model salt concentration profile or gradient inside the membrane. Subsequently, the numerical PDE equation, solved by the forward finite difference (FFD) explicit method, estimated flux decline rates resulted from NaCl fouling. It was found that salt accumulation occurs at the feed-side with a noticeable decrease in flux as fouling increases. Previous works reported similar findings as those identified from our analysis: (1) fouling increases with feed concentration and surface roughness, (2) fouling becomes intensified with higher pressure and flux, (3) fouling from long operation times can reduce flux by 65% within 24 h, (4) NaCl fouling can decrease flux rates by 70% (67-22 LMH) for brackish water with an initial concentration of 10000 ppm, and (5) reversible organic fouling may be avoided from lowering flux rates below the membrane critical flux. Results showed fouled RO modules would decrease flux rates from the increased surface polarization, where reverse flow (negative flux) was estimated for feed-side accumulations >10000 ppm for waters with an initial NaCl concentration of 10000 ppm and average diffusivity of 1.3×10-6 cm2/s. 

 © 2021 The Authors. Published by IASE.

 This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

 Keywords: Membrane separation, Desalination, FFD fouling simulation, Reverse osmosis

 Article History: Received 31 January 2021, Received in revised form 16 April 2021, Accepted 20 April 2021

 Acknowledgment 

The author gratefully appreciates the support provided by the Deanship of Scientific Research at King Abdulaziz University which facilitated the completion of this work.

 Compliance with ethical standards

 Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

 Citation:

 Maddah HA (2021). Simulating fouling impact on the permeate flux in high-pressure membranes. International Journal of Advanced and Applied Sciences, 8(8): 1-8

 Permanent Link to this page

 Figures

 Fig. 1 Fig. 2 Fig. 3 Fig. 4 

 Tables

 Table 1 Table 2 Table 3  

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 References (44)

  1. Alawadhi AA (2002). Regional report on desalination-GCC countries. In the IDA World Congress on Desalination and Water Reuse, Manama, Bahrain: 8-13.   [Google Scholar]
  2. Aleem AEFA, Al-Sugair KA, and Alahmad MI (1998). Biofouling problems in membrane processes for water desalination and reuse in Saudi Arabia. International Biodeterioration and Biodegradation, 41(1): 19-23. https://doi.org/10.1016/S0964-8305(98)80004-8   [Google Scholar]
  3. Al-Hobaib AS, Al-Sheetan KM, Shaik MR, Al-Andis NM, and Al-Suhybani MS (2015). Characterization and evaluation of reverse osmosis membranes modified with Ag2O nanoparticles to improve performance. Nanoscale Research Letters, 10(1): 1-13. https://doi.org/10.1186/s11671-015-1080-3   [Google Scholar] PMid:26428014 PMCid:PMC4883278
  4. AUXIAQUA (2011). Filtration systems: Reverse osmosis. Available online at: http://www.auxiaqua.es/en/sistemas-filtracion/                 
  5. AXEON (2015). Reverse osmosis membrane element construction. AXEON Water Technologies, Temecula, USA.   [Google Scholar]
  6. Baker JS and Dudley LY (1998). Biofouling in membrane systems: A review. Desalination, 118(1-3): 81-89. https://doi.org/10.1016/S0011-9164(98)00091-5   [Google Scholar]
  7. Boo C, Elimelech M, and Hong S (2013). Fouling control in a forward osmosis process integrating seawater desalination and wastewater reclamation. Journal of Membrane Science, 444: 148-156. https://doi.org/10.1016/j.memsci.2013.05.004   [Google Scholar]
  8. Bruggen BV and Vandecasteele C (2002). Distillation vs. membrane filtration: Overview of process evolutions in seawater desalination. Desalination, 143(3): 207-218. https://doi.org/10.1016/S0011-9164(02)00259-X   [Google Scholar]
  9. Chapra SC and Canale RP (2015). Numerical methods for engineers. McGraw-Hill, New York, USA.   [Google Scholar]
  10. Chun Y, Zaviska F, Cornelissen E, and Zou L (2015). A case study of fouling development and flux reversibility of treating actual lake water by forward osmosis process. Desalination, 357: 55-64. https://doi.org/10.1016/j.desal.2014.11.009   [Google Scholar]
  11. Deen WM (2011). Analysis of transport phenomena. 2nd Edition, DEEN Publisher, London, UK.   [Google Scholar]
  12. Drioli E, Criscuoli A, and Curcio E (2002). Integrated membrane operations for seawater desalination. Desalination, 147(1-3): 77-81. https://doi.org/10.1016/S0011-9164(02)00579-9   [Google Scholar]
  13. Field RW, Wu D, Howell JA, and Gupta BBJ (1995). Critical flux concept for microfiltration fouling member. Journal of Membrane Science, 100(3): 259-272. https://doi.org/10.1016/0376-7388(94)00265-Z   [Google Scholar]
  14. Flemming HC (1997). Reverse osmosis membrane biofouling. Experimental Thermal and Fluid Science, 14(4): 382-391. https://doi.org/10.1016/S0894-1777(96)00140-9   [Google Scholar]
  15. Guo W, Ngo HH, and Li J (2012). A mini-review on membrane fouling. Bioresource Technology, 122: 27-34. https://doi.org/10.1016/j.biortech.2012.04.089   [Google Scholar] PMid:22608938
  16. Hegab HM, Wimalasiri Y, Ginic-Markovic M, and Zou L (2015). Improving the fouling resistance of brackish water membranes via surface modification with graphene oxide functionalized chitosan. Desalination, 365: 99-107. https://doi.org/10.1016/j.desal.2015.02.029   [Google Scholar]
  17. Lay WC, Chong TH, Tang CY, Fane AG, Zhang J, and Liu Y (2010). Fouling propensity of forward osmosis: Investigation of the slower flux decline phenomenon. Water Science and Technology, 61(4): 927-936. https://doi.org/10.2166/wst.2010.835   [Google Scholar] PMid:20182071
  18. Li Q, Xu Z, and Pinnau I (2007). Fouling of reverse osmosis membranes by biopolymers in wastewater secondary effluent: Role of membrane surface properties and initial permeate flux. Journal of Membrane Science, 290(1-2): 173-181. https://doi.org/10.1016/j.memsci.2006.12.027   [Google Scholar]
  19. Lonsdale HK, Merten U, and Riley RL (1965). Transport properties of cellulose acetate osmotic membranes. Journal of Applied Polymer Science, 9(4): 1341-1362. https://doi.org/10.1002/app.1965.070090413   [Google Scholar]
  20. Maddah HA (2016a). Optimal operating conditions in designing photocatalytic reactor for removal of phenol from wastewater. ARPN Journal of Engineering and Applied Sciences, 11(3): 1799-1802.   [Google Scholar]
  21. Maddah HA (2016b). Polypropylene as a promising plastic: A review. American Journal of Polymer Science, 6(1): 1-11.   [Google Scholar]
  22. Maddah HA (2016c). Application of finite Fourier transform and similarity approach in a binary system of the diffusion of water in a polymer. Journal of Materials Science and Chemical Engineering, 4(4): 20-30. https://doi.org/10.4236/msce.2016.44003   [Google Scholar]
  23. Maddah HA (2016d). Modeling the relation between carbon dioxide emissions and sea level rise for the determination of future (2100) sea level. American Journal of Environmental Engineering, 6(2): 52-61.   [Google Scholar]
  24. Maddah HA (2018a). Modeling the feasibility of employing solar energy for water distillation. In: Hussain CM (Ed.), Handbook of environmental materials management: 1-25. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-319-58538-3_120-1   [Google Scholar]
  25. Maddah HA (2018b). Analytical derivation of diffusio-osmosis electric potential and velocity distribution of an electrolyte in a fine capillary slit. International Journal of Engineering and Technology, 18(3): 1-9.   [Google Scholar]
  26. Maddah HA (2018c). Numerical analysis for the oxidation of phenol with TiO2 in wastewater photocatalytic reactors. Engineering, Technology and Applied Science Research, 8(5): 3463-3469. https://doi.org/10.48084/etasr.2304   [Google Scholar]
  27. Maddah HA (2019a). Industrial membrane processes for the removal of VOCs from water and wastewater. International Journal of Engineering and Applied Sciences, 6(4): 21–26. https://doi.org/10.31873/IJEAS/6.4.2019.09   [Google Scholar]
  28. Maddah HA (2019b). Modeling and designing of a novel lab-scale passive solar still. Journal of Engineering and Technological Sciences, 51: 303-322. https://doi.org/10.5614/j.eng.technol.sci.2019.51.3.1   [Google Scholar]
  29. Maddah HA (2020a). Adsorption isotherm of NaCl from aqueous solutions onto activated carbon cloth to enhance membrane filtration. Journal of Applied Science and Engineering, 23(1): 69-78.   [Google Scholar]
  30. Maddah HA (2020b). Transport of electrolyte solutions along a plane by diffusion-osmosis. ARPN Journal of Engineering and Applied Sciences, 15: 46-51.   [Google Scholar]
  31. Maddah HA and Alzhrani AS (2017). Quality monitoring of various local and imported brands of bottled drinking water in Saudi Arabia. World Journal of Engineering and Technology, 5(4): 551–563. https://doi.org/10.4236/wjet.2017.54047   [Google Scholar]
  32. Maddah HA and Chogle A (2017). Biofouling in reverse osmosis: Phenomena, monitoring, controlling and remediation. Applied Water Science, 7(6): 2637-2651. https://doi.org/10.1007/s13201-016-0493-1   [Google Scholar]
  33. Maddah HA and Chogle AM (2015). Applicability of low pressure membranes for wastewater treatment with cost study analyses. Membrane Water Treatment, 6(6): 477-488. https://doi.org/10.12989/mwt.2015.6.6.477   [Google Scholar]
  34. Maddah HA and Shihon MA (2018). Activated carbon cloth for desalination of brackish water using capacitive deionization. In: Eyvaz M and Yüksel E (Eds.), Desalination and Water Treatment: 17-36. Books on Demand, Norderstedt, Germany. https://doi.org/10.5772/intechopen.76838   [Google Scholar]
  35. Maddah HA, Alzhrani AS, Almalki AM, Bassyouni M, Abdel-Aziz MH, Zoromba M, and Shihon MA (2017). Determination of the treatment efficiency of different commercial membrane modules for the treatment of groundwater. Journal of Materials and Environmental Science, 8(6): 2006-2012. https://doi.org/10.1007/s13201-018-0793-8   [Google Scholar]
  36. Maddah HA, Alzhrani AS, Bassyouni M, Abdel-Aziz MH, Zoromba M, and Almalki AM (2018). Evaluation of various membrane filtration modules for the treatment of seawater. Applied Water Science, 8(6): 1-13. https://doi.org/10.1007/s13201-018-0793-8   [Google Scholar]
  37. Maddah HA, Bassyouni M, Abdel-Aziz MH, Zoromba MS, and Al-Hossainy AF (2020a). Performance estimation of a mini-passive solar still via machine learning. Renewable Energy, 162: 489-503. https://doi.org/10.1016/j.renene.2020.08.006   [Google Scholar]
  38. Maddah HA, Berry V, and Behura SK (2020b). Cuboctahedral stability in Titanium halide perovskites via machine learning. Computational Materials Science, 173: 109415. https://doi.org/10.1016/j.commatsci.2019.109415   [Google Scholar]
  39. Nguyen TT, Lee C, Field RW, and Kim IS (2020). Insight into organic fouling behavior in polyamide thin-film composite forward osmosis membrane: Critical flux and its impact on the economics of water reclamation. Journal of Membrane Science, 606: 118118. https://doi.org/10.1016/j.memsci.2020.118118   [Google Scholar]
  40. Ogbonmwan SE (2011). Water for life Ireland campaign: Supporting the united nation water campaign. The 2nd United Nation Water day, Expo, Trinity Science Gallery, Dublin, Ireland.   [Google Scholar]
  41. Qureshi BA, Zubair SM, Sheikh AK, Bhujle A, and Dubowsky S (2013). Design and performance evaluation of reverse osmosis desalination systems: An emphasis on fouling modeling. Applied Thermal Engineering, 60(1-2): 208-217. https://doi.org/10.1016/j.applthermaleng.2013.06.058   [Google Scholar]
  42. Rajamohan R, Venugopalan VP, Debasis M, and Usha N (2014). Efficiency of reverse osmosis in removal of total organic carbon and trihalomethane from drinking water. Research Journal of Chemistry and Environment, 18: 1-6.   [Google Scholar]
  43. She Q, Jin X, Li Q, and Tang CY (2012). Relating reverse and forward solute diffusion to membrane fouling in osmotically driven membrane processes. Water Research, 46(7): 2478-2486. https://doi.org/10.1016/j.watres.2012.02.024   [Google Scholar] PMid:22386887
  44. Zhu X and Elimelech M (1997). Colloidal fouling of reverse osmosis membranes: Measurements and fouling mechanisms. Environmental Science and Technology, 31(12): 3654-3662. https://doi.org/10.1021/es970400v   [Google Scholar]