Micellar-enhanced ultrafiltration of zinc in synthetic wastewater using spiral-wound membrane

Role of concentration polarization in cross flow micellar enhanced ultrafiltration of cadmium with low surfactant concentration

Concentration polarization is an important issue in micellar enhanced ultrafiltration (MEUF) of wastewater containing heavy metal ions at low surfactant concentrations. In this paper, we studied removal of Cd(Ⅱ) by cross flow MEUF at low sodium dodecyl sulfate (SDS) concentration levels, and the role of concentration polarization in flux decline and Cd(Ⅱ) rejection was emphasized. Concentration polarization resistance and SDS concentration near membrane were calculated to characterize concentration polarization. The results showed that SDS concentration near membrane was 13 mM when feed concentration was merely 0.8 mM. By combining phase diagram of SDS, structures of SDS micelles in concentration polarization layer were deduced and thin layer structure transformed to porous structure formed by accumulated globular micelles when SDS concentration increased. Although micelles formed in concentration polarization layer was responsible for flux decline, they also provided adsorption sites for Cd(Ⅱ).

Roles of surfactants in pressure-driven membrane separation processes: a review

Surfactants widely exist in various kinds of wastewaters which could be treated by pressure-driven membrane separation (PDMS) techniques. Due to the special characteristics of surfactants, they may affect the performance of membrane filtration. Over the last two decades, there are a number of studies on treating wastewaters containing surfactants by PDMS. The current paper gives a review of the roles of surfactants in PDMS processes. The effects of surfactants on membrane performance were discussed via two aspects: influence of surfactants on membrane fouling and enhanced removal of pollutants by surfactants. The characteristics of surfactants in solution and at solid-liquid interface were summarized. Surfactants in membrane filtration processes cause membrane fouling mainly through adsorption, concentration polarization, pore blocking, and cake formation, and fouling degree may be influenced by various factors (feed water composition, membrane properties, and operation conditions). Furthermore, surfactants may also have a positive effect on membrane performance. Enhanced removal of various kinds of pollutants by PDMS in the presence of surfactants has been summarized, and the removal mechanism has been revealed. Based on the current reports, further studies on membrane fouling caused by surfactants and enhanced removal of pollutants by surfactant-aided membrane filtration were also proposed.

Arsenate removal from aqueous solutions using micellar-enhanced ultrafiltration

In this study, arsenate (As-V) removal using micellar enhanced ultrafiltration (MEUF) modified by cationic surfactants was studied by a dead-end polyacrylonitrile (PAN) membrane apparatus. The UF membrane has been produced by a phase inversion process. The prepared membrane was characterized and analyzed for morphology and membrane properties. The influence of operating parameters such as initial concentrations of As-V, surfactants, pH, membrane thickness, and co-existing anions on the removal of As-V, surfactant rejection, and permeate flux have been studied. The experimental results show that from the two different cationic surfactants used the CPC (cetyl-pyridinium chloride) efficiency (91.7%) was higher than that of HTAB (hexadecyltrimethyl-ammonium bromide) (83.7%). The highest As-V removal was 100%, and was achieved using initial feed concentrations of 100-1000 μg/L, at pH 7 with a membrane thickness of 150 μm in a dead-end filtration system. This efficiency for As-V removal was similar to that obtained using a cross-flow system. Nevertheless, this flux reduction was less than the reduction achieved in the dead-end filtration process. The PAN fabricated membrane in comparison to the RO and NF processes selectively removed the arsenic and the anions, in the water taken from the well, and had no substantial effect on the cations.

Influence of pH on heavy metal speciation and removal from wastewater using micellar-enhanced ultrafiltration

pH plays an important role in heavy metal removal during micellar-enhanced ultrafiltration (MEUF). In the present work, the influence of pH on heavy metal speciation and removal from wastewater by MEUF was investigated using an anionic surfactant (sodium dodecyl sulfate, SDS) and a hydrophilic membrane (polyether sulfone). Experiments were performed with pH values in the range of 1-12. Metal ion removal efficiency (R) was used to assess the effects of the MEUF process. Results showed that better removal rate of copper and cadmium was achieved at high pH values (pH > 3) with SDS feed concentration of 8 mM, while the optimal pH range was 3-10 for zinc and lead. The corresponding efficiencies for heavy metal removal decreased with the increasing feed concentration of metal ions under the pH conditions of 1-12. Furthermore, the heavy metal ion removal rate (50 mg/L) followed the order of Pb²⁺ > Cd²⁺ > Zn²⁺ > Cu²⁺. These results showed that pH is a key parameter in metal ion speciation and removal during MEUF.

Fuzzy modeling and simulation for lead removal using micellar-enhanced ultrafiltration (MEUF)

In the present paper, a three factor, three-level response surface design based on Box-Behnken design (BBD) was developed for maximizing lead removal from aqueous solution using micellar-enhanced ultrafiltration (MEUF). Due to extremely complexity and nonlinearity of membrane separation processes, fuzzy logic (FL) models have been driven to simulate MEUF process under a wide range of initial and hydrodynamic conditions. Instead of using mathematical model, fuzzy logic approach provides a simpler and easier approach to describe the relationships between the processing variables and the metal rejection and permeation flux. Statistical values, which quantify the degree of agreement between experimental observations and numerically calculated values, were found greater than 91% for all cases. The results show that predicted values obtained from the fuzzy model were in very good agreement with the reported experimental data.