Water Science and Technology (Nov 2021)

Enhanced modelling and experimental validation of ultra-low pressure reverse osmosis membrane system for treatment of synthetic brackish water

  • Saffa Syamimi Norizam,
  • Mohd Azlan Hussain,
  • Mohd Usman Mohd Junaidi

DOI
https://doi.org/10.2166/wst.2021.442
Journal volume & issue
Vol. 84, no. 10-11
pp. 3372 – 3387

Abstract

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Water purification from brackish water sources has been acknowledged as one of the most promising ways to produce drinkable water in water-scarce areas. In this study, an ultra-low pressure reverse osmosis (ULPRO) membrane was numerically and experimentally investigated to produce drinking water by the removal of sodium chloride salt which provides further validation of the model from a practical perspective. An enhanced predictive model based on the Donnan–Steric Pore Model with dielectric exclusion (DSPM-DE) incorporating the osmotic effects was formulated in process simulation. The feed pressure and concentration were optimized as input variables and interaction between them was observed, while salt rejection and water recovery rate were taken as response attributes. The results obtained on the ULPRO membrane showed that the performance depends on the charge, steric, and dielectric effects. Furthermore, the enhanced model was validated with the experimental data attained from a laboratory-scale filtration system with good accuracy in the salt rejection and water recovery results. Comparing the enhanced DSPM-DE with the existing solution diffusion model reveals that the enhanced model predicts the membrane performance better and thereby qualifies itself as a reliable model for desalination of brackish water using ULPRO membrane. HIGHLIGHTS An enhanced DSPM with a dielectric exclusion model for ULPRO membrane is developed.; Predicted ULPRO membrane performance for low operating pressure of 1 to 4 bar.; Predicted ULPRO membrane performance for brackish water at salinity up to 2,000 ppm.; Model validated through experimental data for salt rejection and water recovery with good accuracy.; Enhanced model predicts salt rejection better than using solution diffusion model.;

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