Response surface methodology to investigate the effects of operational parameters on membrane fouling and organic matter rejection in hard-shell encased hollow-fiber membrane

Electro-Conductive Modification of Polyvinylidene Fluoride Membrane for Electrified Wastewater Treatment: Optimization and Antifouling Performance

Electro-conductive membranes coupled with a low-voltage electric field can enhance pollutant removal and mitigate membrane fouling, demonstrating significant potential for electrified wastewater treatment. However, efficient fabrication of conductive membranes poses challenges. An in situ oxidative polymerization approach was applied to prepare PVDF-based conductive membranes (PVDF-CMs) and response surface methodology (RSM) was adopted to optimize modification conditions enhancing membrane performance. The anti-fouling property of the conductive membranes was analyzed using model pollutants. The results indicate that when the concentrations of the pyrrole, BVIMBF4, and FeCl3·6H2O are 0.9 mol/L, 4.8 mmol, and 0.8 mol/L, respectively, the electrical resistance of the PVDF-CM is 93 Ω/sq with the water contact angle of 31°, demonstrating good conductivity and hydrophilicity. Batch membrane filtration experiments coupled with negative voltage indicated that when an external voltage of 2.0 V is applied, membrane fouling rates for the conductive membrane filtering BSA and SA solutions are reduced by 17.7% and 17.2%, respectively, compared to the control (0 V). When an external voltage of 0.5 V is applied, the membrane fouling rate for the conductive membrane filtering HA solution is reduced by 72.6%. This study provides a valuable reference for the efficient preparation of conductive membranes for cost-effective wastewater treatment.

A Novel Modeling Optimization Approach for a Seven-Channel Titania Ceramic Membrane in an Oily Wastewater Filtration System Based on Experimentation, Full Factorial Design, and Machine Learning

This comprehensive study looks at how operational conditions affect the performance of a novel seven-channel titania ceramic ultrafiltration membrane for the treatment of produced water. A full factorial design experiment (23) was conducted to study the effect of the cross-flow operating factors on the membrane permeate flux decline and the overall permeate volume. Eleven experimental runs were performed for three important process operating variables: transmembrane pressure (TMP), crossflow velocity (CFV), and filtration time (FT). Steady final membrane fluxes and permeate volumes were recorded for each experimental run. Under the optimized conditions (1.5 bar, 1 m/s, and 2 h), the membrane performance index demonstrated an oil rejection rate of 99%, a flux of 297 L/m2·h (LMH), a 38% overall initial flux decline, and a total permeate volume of 8.14 L. The regression models used for the steady-state membrane permeate flux decline and overall permeate volume led to the highest goodness of fit to the experimental data with a correlation coefficient of 0.999. A Multiple Linear Regression method and an Artificial Neural Network approach were also employed to model the experimental membrane permeate flux decline and analyze the impact of the operating conditions on membrane performance. The predictions of the Gaussian regression and the Levenberg-Marquardt backpropagation method were validated with a determination coefficient of 99% and a Mean Square Error of 0.07.

Optimization of photocatalytic ceramic membrane filtration by response surface methodology: Effects of hydrodynamic conditions on organic fouling and removal efficiency

The effects of the operating conditions, including the applied pressure, feed organic concentration, and recirculation flowrate along the TiO2-coated ceramic membrane, on the normalized membrane permeability and organic removal efficiency were systematically investigated by operating a photocatalytic membrane reactor (PMR). Response surface methodology (RSM) was conducted to better understand the interactive effect of operational conditions as well as their individual and combined effects to control membrane performance. Our results showed that the applied pressure and feed organic concentration, as single parameter, affected the normalized membrane permeability and organic removal efficiency more dominantly than the recirculation flowrate. The polynomial performance equations generated by RSM successfully predicted the membrane performance of the PMR. The responses to the normalized membrane permeability and organic removal efficiency with respect to the operational conditions were less sensitive to any combination of operational conditions than to their individual impacts. The combined effects of the operating conditions were less pronounced in promoting the catalytic performance of organic contaminants on the TiO2 surface. Our RSM analysis based on experimental observations designed by Box-Behnken Design (BBD) suggested that 1.3 bar of applied pressure, 44 mg/L of feed organic dye concentration and 0.8 L/min as recirculation flowrate as optimum conditions achieved more than 98% of organic removal efficiency and less than 5% of decline in normalized membrane permeability. This research shows that the RSM provides effective tool to optimize operational conditions to determine fouling rate and organic removal in PMR.

Existing Filtration Treatment on Drinking Water Process and Concerns Issues

Water is one of the main sources of life's survival. It is mandatory to have good-quality water, especially for drinking. Many types of available filtration treatment can produce high-quality drinking water. As a result, it is intriguing to determine which treatment is the best. This paper provides a review of available filtration technology specifically for drinking water treatment, including both conventional and advanced treatments, while focusing on membrane filtration treatment. This review covers the concerns that usually exist in membrane filtration treatment, namely membrane fouling. Here, the parameters that influence fouling are identified. This paper also discusses the different ways to handle fouling, either based on prevention, prediction, or control automation. According to the findings, the most common treatment for fouling was prevention. However, this treatment required the use of chemical agents, which will eventually affect human health. The prediction process was usually used to circumvent the process of fouling development. Based on our reviews up to now, there are a limited number of researchers who study membrane fouling control based on automation. Frequently, the treatment method and control strategy are determined individually.

Fouling and chemically enhanced backwashing performance of low-pressure membranes during the treatment of shale gas produced water

The treatment of shale gas produced water (SGPW) for beneficial reuse is currently the most dominant and economical option. Membrane filtration is one preferred method to deal with SGPW, but membrane fouling is an unavoidable problem. In this study, two types of ultrafiltration (UF) membranes and one type of microfiltration (MF) membrane were investigated to treat SGPW from Sichuan basin. Results showed that increased total dissolved solid (31-40 g/L) and UV₂₅₄ (10-42.9 m^-1) were observed for the same shale gas plays, and the primary fluorescent organic substances were humic acid-like components. Compared to UF membranes with the flux decline by 2% to 60%, MF membranes with larger pore size were more likely to be fouled with the flux decline by 43% to 95%. Cake layer filtration was verified to be the primary membrane fouling mechanism. Statistical analysis showed that UV₂₅₄ played the most significant role in membrane fouling which had the highest correlation (0.76 to 0.93). Compared to permeate backwashing (13%), deionized water backwashing and chemically enhanced backwashing (CEB) using NaClO, H₂O₂ and citric acid improved the cleaning efficiencies (31%-95%). CEB using NaOH prepared by deionized water aggravated membrane fouling, while excellent cleaning efficiencies (39%-79%) were observed for CEB using NaOH prepared by permeate. The difference in cleaning behaviors for fouled membranes by SGPW was verified by morphology observation and element composition analysis.

Characterization and flocculation performance of a newly green flocculant derived from natural bagasse cellulose

A newly green natural polymer bagasse cellulose based flocculant (PBCF) was synthesized utilizing a grafting copolymerization method for effectively enhancing humic acid (HA) removal from natural water. This work aims to investigate flocculation behavior of PBCF in synthetic water containing HA, and the effects of flocculant dose and initial solution pH on flocculation performance. Results showed that PBCF functioned well at a flocculant dose of 60 mg/L and pH ranging from 6.0 to 9.0. The organic removal efficiency in synthetic water in terms of HA (UV₂₅₄) and chemical oxygen demand (COD _Mn) were up to 90.6% and 91.3%, respectively. Furthermore, the charge neutralization and adsorption bridging played important roles in HA removal. When applied for lake water, PBCF removed 91.6% turbidity and 50.0% dissolved organic matter, respectively. In short, PBCF demonstrates great potential in water treatment in a safe and environmentally friendly or 'green' way.

Optimization of Nanofiltration Hollow Fiber Membrane Fabrication Process Based on Response Surface Method

Layer-by-layer (LBL) self-assembly technology has become a new research hotspot in the fabrication of nanofiltration membranes in recent years. However, there is a lack of a systematic approach for the assessment of influencing factors during the membrane fabrication process. In this study, the process optimization of LBL deposition was performed by a two-step statistical method. The multiple linear regression was performed on the results of single-factor experiments to determine the major influencing factors on membrane performance, including the concentration of Poly (allylamine hydrochloride) (PAH), glutaraldehyde, and the NaCl concentration in PAH solution. The Box–Behnken response surface method was then used to analyze the interactions between the selected factors, while their correlation with the membrane performance was obtained by polynomial fitting. The R² value of the regression models (0.97 and 0.94) was in good agreement with the adjusted R² value (0.93 and 0.86), indicating that the quadratic response models were adequate enough to predict the membrane performance. The optimal process parameters were finally determined through dual-response surface analysis to achieve both high membrane permeability of 14.3 LMH·MPa⁻¹ and MgSO₄ rejection rate of 90.22%.