Pressure-driven membranes for advanced treatment of textile wastewater: Dye/salt fractionation, concentration, and cleaning strategies

Textile wastewater commonly contains various organic compounds and salt mixtures, potentially raising serious environmental and health concerns. Traditional treatment approaches are hindered by high salinity; consequently, membrane separation technologies have attracted increasing attention over the past few decades. Herein, four commercial pressure-driven membranes with molecular weight cut-off (MWCO) gradients were employed for the advanced treatment of different types of textile wastewater. Specifically, these membranes were initially subjected to a fractionation test toward the dye/salt mixtures, followed by deep concentration of the dye molecules. Using Congo red (CR), methyl blue (MB), NaCl, and Na2SO4 as representative dyes and salts, the results indicated that all membranes could effectively separate dye/salt mixtures and further conduct a deep concentration process toward the separated dye solutions. However, their efficiency and effectiveness largely depend on the membrane pore size and solution characteristics. For instance, membranes with lower MWCOs experience less fouling and shorter operation durations when treating CR-related solutions. All membranes showed improved fractionation efficiency toward MB/salt mixtures, requiring only approximately 10.2–42.9 % of the operation duration compared to CR-related solutions. The loose nanofiltration membrane proved superior to tight ultrafiltration membranes in both fractionation and concentration processes. Further research on cleaning methodologies demonstrated that both alkali and ethanol cleaning were influential in restoring the membrane performance. An appropriate ethanol/water concentration can effectively regenerate severely fouled membranes, achieving a high flux recovery ratio of ~95 %. This study evaluated state-of-the-art pressure-driven membranes for textile wastewater treatment and guided cleaning strategies for optimal performance recovery.