Build-up of a continuous flow pre-coated dynamic membrane filter to treat diluted textile wastewater and identify its dynamic membrane fouling.

This research built up a continuous dynamic flow filter membrane to treat diluted textile wastewater and basically investigated dynamic membrane fouling mechanism. By pre-depositing particles activated carbon (PAC) on membrane support material (MSM), a thin layer was formed on its surface, which showed excellent results in removing organic pollutants from diluted textile wastewater. Experimental data were regressed by the Langmuir, Freundlich, Temkin, Dubinin-Radushkevich (D-R) and Sips isotherm models. The three two-parameter isotherms (Temkin, D-R and Freundlich) were the models that best fitted, with respectively 0.977, 0.975 and 0.973 regression coefficients. D-R model has registered the maximum calculated adsorption capacity Qmd, cal. = 45.499 mg/g and the mean energy which was required to adsorb 1 mol of MB dye by the DM layer E = 4.249 kJ/mol; indicating the energy distribution onto heterogeneous surface of a physical adsorption process. Furthermore, kinetic models results showed that MB adsorption onto PAC at different initial concentrations follows the pseudo-second order. The obtained results also indicated that a flexible DM layer with different thickness can be formed from different amount of PAC pre-deposited on MSMs, which demonstrated that it was convenient to adjust the required DM thickness to filtrate a known initial concentration for >99% organic pollutants removal efficiency rate. However, DM fouling occurred on small pores MSMs; which resulted in an increase of the filtration pressure what have affected the filtration performance. PAC and MSMs surface morphology and texture structure, before and after filtration, were visualized respectively by Field Emission Scanning Electron Microscopy (FESEM), Fourier Transform Infra-Red and Attenuated Total Reflectance (FTIR/ATR). From these experimental results, a sustainable flux (>6.85 × 10-5 m/s) was established to discriminate no fouling from fouling conditions based on flux and TMP trends variance.