Influences of temperature on the retention of PPCPs by nanofiltration membranes: Experiments and modeling assessment

Application of high-dose UV irradiation as nanofiltration pretreatment for drinking water production: Organic fouling mitigation and micropollutant removal

Nanofiltration (NF) is being increasingly applied to produce high-quality drinking water; however, its cost-effective operation remains challenging due to the perennial membrane fouling. On account of the low tolerance of common NF membranes to chemical oxidants, this study proposed high-dose UV irradiation as a pretreatment strategy for organic fouling mitigation. Results showed that the permeate flux decline of the membrane with UV-treated feedwater (with a dose of 750 mJ cm-2) was less drastic than that with raw feedwater, but slightly faster as compared to that with UV/Cl2 pretreatment. The final normalized fluxes were 0.69, 0.79, and 0.82, respectively, after 10 h of operation with raw, UV- and UV/Cl2-treated feedwaters. With the characterization of feedwaters and membranes, the fouling was found to be initiated by the adsorption of hydrophilic biopolymers onto the membrane, followed by the deposition of hydrophobic humic substances. Reduction of the "glue" biopolymers was crucial to membrane fouling mitigation. The applicability of UV pretreatment in practice was testified with a pilot-scale UV-NF system where permeate flux of the NF module decreased by 37% after six-week continuous operation. Moreover, UV pretreatment could remove most of the identified pesticides in the feedwater with a removal efficiency over 80% for metolachlor and imidacloprid, but had no or even a negative effect on perfluorinated compounds. This work discloses the efficacy and mechanism of high-dose UV irradiation for NF membrane fouling control, which facilitates future research and application of NF technology.

Micropollutant rejection by nanofiltration membranes: A mini review dedicated to the critical factors and modelling prediction

Nanofiltration (NF) membranes, extensively used in advanced wastewater treatment, have broad application prospects for the removal of emerging trace organic micropollutants (MPs). The treatment performance is affected by several factors, such as the properties of NF membranes, characteristics of target MPs, and operating conditions of the NF system concerning MP rejection. However, quantitative studies on different contributors in this context are limited. To fill the knowledge gap, this study aims to assess critical impact factors controlling MP rejection and develop a feasible model for MP removal prediction. The mini-review firstly summarized membrane pore size, membrane zeta potential, and the normalized molecular size (λ = rs/rp), showeing better individual relationships with MP rejection by NF membranes. The Lindeman-Merenda-Gold model was used to quantitatively assess the relative importance of all summarized impact factors. The results showed that membrane pore size and operating pressure were the high impact factors with the highest relative contribution rates to MP rejection of 32.11% and 25.57%, respectively. Moderate impact factors included membrane zeta potential, solution pH, and molecular radius with relative contribution rates of 10.15%, 8.17%, and 7.83%, respectively. The remaining low impact factors, including MP charge, molecular weight, logKow, pKa and crossflow rate, comprised all the remaining contribution rates of 16.19% through the model calculation. Furthermore, based on the results and data availabilities from references, the machine learning-based random forest regression model was trained with a relatively low root mean squared error and mean absolute error of 12.22% and 6.92%, respectively. The developed model was then successfully applied to predict MPs' rejections by NF membranes. These findings provide valuable insights that can be applied in the future to optimize NF membrane designs, operation, and prediction in terms of removing micropollutants.

A Review of Temperature Effects on Membrane Filtration

Membrane technology plays a vital role in drinking water and wastewater treatments. Among a number of factors affecting membrane performance, temperature is one of the dominant factors determining membrane performance. In this review, the impact of temperature on membrane structure, fouling, chemical cleaning, and membrane performance is reviewed and discussed with a particular focus on cold temperature effects. The findings from the literature suggest that cold temperatures have detrimental impacts on membrane structure, fouling, and chemical cleaning, and thus could negatively affect membrane filtration operations and performance, while warm and hot temperatures might expand membrane pores, increase membrane flux, improve membrane chemical cleaning efficiency, and interfere with biological processes in membrane bioreactors. The research gaps, challenges, and directions of temperature effects are identified and discussed indepth. Future studies focusing on the impact of temperature on membrane processes used in water and wastewater treatment and the development of methods that could reduce the adverse effect of temperature on membrane operations are needed.

Pressure-driven membrane filtration technology for terminal control of organic DBPs: A review

Disinfection by-products (DBPs), a series of undesired secondary contaminants formed during the disinfection processes, deteriorate water quality, threaten human health and endanger ecological safety. Membrane-filtration technologies are commonly used in the advanced water treatment and have shown a promising performance for removing trace contaminants. In order to gain a clearer understanding of the behavior of DBPs in membrane-filtration processes, this work dedicated to: (1) comprehensively reviewed the retention efficiency of microfiltration (MF), ultrafiltration (UF), nanofiltration (NF) and reverse osmosis (RO) for DBPs. (2) summarized the mechanisms involved size exclusion, electrostatic repulsion and adsorption in the membrane retention of DBPs. (3) In conjunction with principal component analysis, discussed the influence of various factors (such as the characteristics of membrane and DBPs, feed solution composition and operating conditions) on the removal efficiency. In general, the characteristics of the membranes (salt rejection, molecular weight cut-off, zeta potential, etc.) and DBPs (molecular size, electrical property, hydrophobicity, polarity, etc.) fundamentally determine the membrane-filtration performance on retaining DBPs, and the actual operating environmental factors (such as solute concentration, coexisting ions/NOMs, pH and transmembrane pressure) exert a positive/negative impact on performance to some extent. Current researches indicate that NF and RO can be effective in removing DBPs, and looking forward, we recommend that multiple factors should be taken into account that optimize the existed membrane-filtration technologies, rationalize the selection of membrane products, and develop novel membrane materials targeting the removal of DBPs.

Resource recovery from RO concentrate using nanofiltration: Impact of active layer thickness on performance

Modelling the removal of monovalent and divalent ions from seawater via nanofiltration is crucial for pre-treatment in seawater reverse osmosis systems. Effective separation of divalent ions through nanofiltration and allowing the permeate containing only monovalent ions to pass through the reverse osmosis system produces pure NaCl salt from the concentrate. However, the Donnan steric pore model and dielectric exclusion assume a uniformly distributed cylinder pore morphology, which is not representative of the actual membrane structure. This study analyzed the impact of membrane thickness on neutral solute removal and investigated the effect of two different methods for calculating the Peclet number on rejection rates of monovalent and divalent salts. Results show that membrane thickness has a significant effect on rejection rates, particularly for uncharged solutes in the range of 0.5-0.7 solute radius to membrane pore size ratio. Operating pressures above 10 bar favour the use of effective active layer thickness over the membrane pore size to calculate the Peclet number. At low pressures, using the effective active layer can lead to overestimation of monovalent salt rejection and underestimation of divalent salt rejection. This study highlights the importance of appropriate Peclet number calculation methods based on applied pressure when modelling membrane separation performance.

Experiments and machine learning-based modeling for haloacetic acids rejection by nanofiltration: Influence of solute properties and operating conditions

Because of potential risks to public health, the presence of haloacetic acids (HAAs) in drinking water is a major concern. Nanofiltration (NF) has shown potential for HAAs rejection, and several factors, namely, membrane properties, solute properties, and operating conditions, have been revealed key roles. However, knowledge of NF separation mechanism by quantifying these factors is limited. This study investigated and modeled NF performance on HAAs rejection. NF performance was experimentally investigated under various transmembrane pressure (TMP), cross-flow velocity (CV), temperature, pH, ionic strength (IS), and HAAs initial feed concentration (C_in). We used machine learning (ML) to understand the mechanism from the perspective of HAAs properties and operating conditions. Multiple linear regression (MLR), support vector machine (SVM), multsilayer perceptron (MLP), extreme gradient boosting (XGBoost), and random forest (RF) models were used. The MLP, XGBoost and RF models achieved significant performance with high R² (0.970, 0.973, and 0.980) and low RMSE (4.71, 4.41, and 3.84). These three models were analyzed using the Shapley Additive explanation (SHAP) to quantify relative contributions of HAAs properties and operating conditions. XGBoost-SHAP produced the most logical results and was the best-performing model for selecting optimal input variables combinations. The results showed that Stokes radius (r_s), logarithmic octanol-water partitioning coefficient (logK_ow), molecular weight (MW), pH, TMP, and temperature are key variables for interpreting NF process. The effects of HAAs properties were ranked as r_s > logK_ow > MW, suggesting significance of size exclusion and hydrophobic interaction. The impact of the operational conditions followed the order pH > TMP > temperature, illustrating that pH was the major influencing operating condition. This study demonstrated significant capacity of ML, which reduced amount of experimental work. In addition, the main operating conditions can be evaluated in terms of their contributions, making ML an efficient tool for risk management and process optimization.

Boosting the Performance of Nanofiltration Membranes in Removing Organic Micropollutants: Trade-Off Effect, Strategy Evaluation, and Prospective Development

In view of the high risks brought about by organic micropollutants (OMPs), nanofiltration (NF) processes have been playing a vital role in advanced water and wastewater treatment, owing to the high membrane performance in rejection of OMPs, permeation of water, and passage of mineral salts. Though numerous studies have been devoted to evaluating and technically enhancing membrane performance in removing various OMPs, the trade-off effect between water permeance and water/OMP selectivity for state-of-the-art membranes remains far from being understood. Knowledge of this effect is significant for comparing and guiding membrane development works toward cost-efficient OMP removal. In this work, we comprehensively assessed the performance of 88 NF membranes, commercialized or newly developed, based on their water permeance and OMP rejection data published in the literature. The effectiveness and underlying mechanisms of various modification methods in tailoring properties and in turn performance of the mainstream polyamide (PA) thin-film composite (TFC) membranes were quantitatively analyzed. The trade-off effect was demonstrated by the abundant data from both experimental measurements and machine learning-based prediction. On this basis, the advancement of novel membranes was benchmarked by the performance upper-bound revealed by commercial membranes and lab-made PA membranes. We also assessed the potentials of current NF membranes in selectively separating OMPs from inorganic salts and identified the future research perspectives to achieve further enhancement in OMP removal and salt/OMP selectivity of NF membranes.

Rejection of trace organic compounds by membrane processes: mechanisms, challenges, and opportunities

This work critically reviews the application of various membrane separation processes (MSPs) in treating water polluted with trace organic compounds (TOrCs) paying attention to nanofiltration (NF), reverse osmosis (RO), membrane bioreactor (MBR), forward osmosis (FO), and membrane distillation (MD). Furthermore, the focus is on loopholes that exist when investigating mechanisms through which membranes reject/retain TOrCs, with the emphasis on the characteristics of the model TOrCs which would facilitate the identification of all the potential mechanisms of rejection. An explanation is also given as to why it is important to investigate rejection using real water samples, especially when aiming for industrial application of membranes with novel materials. MSPs such as NF and RO are prone to fouling which often leads to lower permeate flux and solute rejection, presumably due to cake-enhanced concentration polarisation (CECP) effects. This review demonstrates why CECP effects are not always the reason behind the observed decline in the rejection of TOrCs by fouled membranes. To mitigate for fouling, researchers have often modified the membrane surfaces by incorporating nanoparticles. This review also attempts to explain why nano-engineered membranes have not seen a breakthrough at industrial scale. Finally, insight is provided into the possibility of harnessing solar and wind energy to drive energy intensive MSPs. Focus is also paid into how low-grade energy could be stored and applied to recover diluted draw solutions in FO mode.

Nitrogen-doped carbon nanosheets with Fe-based nanoparticles for highly efficient degradation of antibiotics and sulfate ion enhancement effect

Developing Fe-based catalysts with high-effective and environmentally friendly features in Fenton-like system for treating wastewater is still a challenge. Novel nitrogen-doped carbon nanosheets with Fe⁰/Fe₃C nano-particles (Fe@NCS-900) were prepared through a simple solvent-free strategy by pyrolyzing the mixture of 2,6-diaminopyridine and ferric chloride hexahydrate under 900 °C. The Fe@NCS-900 possessed almost 100% removal efficiency and 66.5% mineralization rate for the degradation of CBZ in 10 min. Moreover, the Fe@NCS-900 exhibited an apparent first-order constant as high as 0.8809 min^-1, which is 22 and 29 times higher than that of the commercial Fe⁰ and traditional Fenton system, respectively, which could be attribute to the high graphitization degree and rich nitrogen content. Besides, the results of the radical quenching experiments, electron paramagnetic resonance (EPR) and the probe experiments demonstrated that a large number of high valent iron species (Fe (IV)) besides singlet oxygen (¹O₂) and superoxide radicals (O₂^•-) existed and contributed to the CBZ degradation. More interestingly, the addition of coexisting anion SO₄^2- in the reaction system could significantly boost the concentration of •OH and SO₄^•- by 28.3 times and 9.7 times, respectively, resulting in the increase of the apparent first-order constant by 5.9 times (5.1733 min^-1), which was entirely different from previous reports that SO₄^2- had no effect on the catalytic activity or even displayed slightly inhibitory effect. In addition, the catalyst exhibited broad pH adaptability in the pH range of 2-9. The intermediate products of CBZ degradation were investigated by liquid chromatography mass spectrometry (LC-MS) and the degradation pathway was proposed. This paper provides new insights for developing a promising Fe-based nitrogen-doped catalyst for practical wastewater treatment.

Tailored design of nanofiltration membranes for water treatment based on synthesis-property-performance relationships

Tailored design of high-performance nanofiltration (NF) membranes is desirable because the requirements for membrane performance, particularly ion/salt rejection and selectivity, differ among the various applications of NF technology ranging from drinking water production to resource mining. However, this customization greatly relies on a comprehensive understanding of the influence of membrane fabrication methods and conditions on membrane properties and the relationships between the membrane structural and physicochemical properties and membrane performance. Since the inception of NF, much progress has been made in forming the foundation of tailored design of NF membranes and the underlying governing principles. This progress includes theories regarding NF mass transfer and solute rejection, further exploitation of the classical interfacial polymerization technique, and development of novel materials and membrane fabrication methods. In this critical review, we first summarize the progress made in controllable design of NF membrane properties in recent years from the perspective of optimizing interfacial polymerization techniques and adopting new manufacturing processes and materials. We then discuss the property-performance relationships based on solvent/solute mass transfer theories and mathematical models, and draw conclusions on membrane structural and physicochemical parameter regulation by modifying the fabrication process to improve membrane separation performance. Next, existing and potential applications of these NF membranes in water treatment processes are systematically discussed according to the different separation requirements. Finally, we point out the prospects and challenges of tailored design of NF membranes for water treatment applications. This review bridges the long-existing gaps between the pressing demand for suitable NF membranes from the industrial community and the surge of publications by the scientific community in recent years.

Alternanthera spp. based-phytoremediation for the removal of acetaminophen and methylparaben at mesocosm-scale constructed wetlands

Recently, the spread of pharmaceuticals and personal care products (PPCPs) in the aquatic environment has steadily increased. In this study, phytoremediation technology, using an ornamental plant (Alternanthera spp.), was investigated to improve the removal of acetaminophen (AC) and methylparaben (MP) from a synthetically prepared wastewater. Three exposure lines (AC-line, MP-line and control-line) were performed with a total of 26 subsurface-horizontal constructed wetlands (SSH-CWs) that operated in batch feeding mode. The influence of plants in addition to the initial spiking concentration (20, 60 and 100 mg/L) of AC and MP on the removal efficiency was evaluated throughout the 35-days experiments. The highest removal efficiencies for AC and MP were 88.6% and 66.4%, respectively, achieved in the planted CWs; whereas only 29.7% and 21.9% were achieved in the control CWs for AC and MP, respectively. The results confirmed the role of Alternanthera spp. for accelerating the removal of AC and MP from synthetically contaminated wastewater in CWs.

Adsorption and fouling behaviors of customized nanocomposite membrane to trace pharmaceutically active compounds under multiple influent matrices

Rare information is available on fouling behavior of customized nanofiltration (NF) membrane evoked by pharmaceutically active compounds (PhACs) under real multiple influent matrices pretreated by ultrafiltration module beforehand. To this end, a novel tight NF membrane with excellent perm-selectivity and antiadhesion was fabricated and used to assess its separation performance/mechanism and fouling behavior to a broad range of small molecular PhACs in the context. The adsorption ratio results revealed that the affinities between five selected PhACs and the customized nanocomposite membrane surface were all much weaker (below 5.5%) than the solute-solute interacting forces (between 23.6 and 83.2%), whether for natural or synthetic complex micropollutants. The predominant membrane fouling could be interpreted by the incomplete blocking model in the permeation of both influent conditions. For neat nanocomposite membrane, the order of critical factors important on separation mechanism was electrostatic effect, adsorption and steric hindrance. The fouling layer seemed to act as a secondary separating layer for those negatively charged or hydrophilic PhACs, but showed the cake enhanced concentration polarization effect for the neutral and hydrophobic ones. This study provides valuable insights for defining PhACs fate and NF membrane fouling behavior to fit increasingly stringent criteria for wastewater treatment.

Predicting Micropollutant Removal by Reverse Osmosis and Nanofiltration Membranes: Is Machine Learning Viable?

Predictive models for micropollutant removal by membrane separation are highly desirable for the design and selection of appropriate membranes. While machine learning (ML) models have been applied for such purposes, their reliability might be compromised by data leakage due to inappropriate data splitting. More importantly, whether ML models can truly understand the mechanisms of membrane separation has not been revealed. In this study, we evaluate the capability of the XGBoost model to predict micropollutant removal efficiencies of reverse osmosis and nanofiltration membranes. Our results demonstrate that data leakage leads to falsely high prediction accuracy. By utilizing a model interpretation method based on the cooperative game theory, we test the knowledge of XGBoost on the mechanisms of membrane separation via quantifying the contributions of input variables to the model predictions. We reveal that XGBoost possesses an adequate understanding of size exclusion, but its knowledge of electrostatic interactions and adsorption is limited. Our findings suggest that future work should focus more on avoiding data leakage and evaluating the mechanistic knowledge of ML models. In addition, high-quality data from more diverse experimental conditions, as well as more informative variables, are needed to improve the accuracy of ML models for predicting membrane performance.

Influences of Technological Parameters on Cross-Flow Nanofiltration of Cranberry Juice

The paper focused on the influence of operative conditions on the separation of benzoic acid from 10 °Brix cranberry juice by cross-flow nanofiltration with a plate and frame pilot scale (DDS Lab Module Type 20 system). Six kinds of commercial nanofiltration membrane were investigated. The results showed that the rejection of benzoic acid was significantly lower than that of other components in cranberry juice, including sugars and other organic acids. In a range of 2-7.5 L/min, feed flow rate slightly affected the performance of nanofiltration. Higher temperatures resulted in higher permeate flux and lower rejection of benzoic acid, whereas rejection of sugar and organic acid was stable at a high value. In a range of 2.5-5.5, pH also significantly affected the separation of benzoic acid and negative rejection against benzoic acid was observed at pH 4.5 with some of the membranes. This implies that pH 4.5 is considered as an optimum pH for benzoic acid separation from cranberry juice. The lower permeate flux caused a lower rejection of benzoic acid and negative rejection of benzoic acid was observed at the low permeate flux. Pretreatment by ultrafiltration with CR61PP membranes could improve the permeate flux but insignificantly influenced the efficiency of separation. The results also indicated that NF99 and DK membranes can be effectively used to separate benzoic acid from cranberry juice.

Modeling of Nanofiltration Process Using DSPM-DE Model for Purification of Amine Solution

The formation of heat stable salts (HSS) during the natural gas sweetening process by amine solvent causes many problems such as corrosion, foaming, capacity reduction, and amine loss. A modeling study was carried out for the removal of HSS ions from amine solution using nanofiltration (NF) membrane process that ensures the reuse of amine solution for gas sweetening. This model studies the physics of the nanofiltration process by adjusting and investigating pore radius, the effects of membrane charge, and other membrane characteristics. In this paper, the performance of the ternary ions was investigated during the removal process from methyl di-ethanol amine solution by the nanofiltration membrane process. Correlation between feed concentration and permeate concentration, using experimental results with mathematical correlation as Ci,p = f (Ci,f) was used in modeling. The results showed that the calculated data from the model provided a good agreement with experimental results (R2 = 0.90-0.75). Also, the effect of operating conditions (including feed pressure and feed flow rate on ions rejection and recovery ratio across the flat-sheet membrane) was studied. The results showed that the recovery and rejection ratios of the NF membrane depend on the driving pressure across the membrane. While the driving pressure is affected by the feed flow conditions and feed pressure.

Recent Advances in the Rejection of Endocrine-Disrupting Compounds from Water Using Membrane and Membrane Bioreactor Technologies: A Review

Water is a critical resource necessary for life to be sustained, and its availability should be secured, appropriated, and easily obtainable. The continual detection of endocrine-disrupting chemicals (EDCs) (ng/L or µg/L) in water and wastewater has attracted critical concerns among the regulatory authorities and general public, due to its associated public health, ecological risks, and a threat to global water quality. Presently, there is a lack of stringent discharge standards regulating the emerging multiclass contaminants to obviate its possible undesirable impacts. The conventional treatment processes have reportedly ineffectual in eliminating the persistent EDCs pollutants, necessitating the researchers to develop alternative treatment methods. Occurrences of the EDCs and the attributed effects on humans and the environment are adequately reviewed. It indicated that comprehensive information on the recent advances in the rejection of EDCs via a novel membrane and membrane bioreactor (MBR) treatment techniques are still lacking. This paper critically studies and reports on recent advances in the membrane and MBR treatment methods for removing EDCs, fouling challenges, and its mitigation strategies. The removal mechanisms and the operating factors influencing the EDCs remediation were also examined. Membranes and MBR approaches have proven successful and viable to eliminate various EDCs contaminants.

Enhanced micropollutants removal by nanofiltration and their environmental risks in wastewater reclamation: A pilot-scale study

The emerging contaminants, in particular pharmaceuticals and personal care products and environmental estrogens, have been received global concerns in recent years. Nanofiltration (NF) as an advanced tertiary treatment technology can be a reliable and potential tool for micropollutants removal. However, the influence of operation conditions of NF system to micropollutants rejections in an engineering application, is still lacking. Here, a pilot-scale NF system was set up to investigate its removal efficiencies to 49 micropollutants under different operation conditions by treating actual municipal wastewater. The results showed that the rejections of positively and neutrally charged micropollutants with molecular weight higher than 250 g mol^-1 were both higher than 80%. Besides, most negatively charged micropollutants were also rejected higher than 80% under different operation conditions. The rejections of most micropollutants increased with temperature decreased from 25 °C to 13 °C, which was primarily ascribed to decrease of pore size of NF membrane at low temperature. Compared with the water recovery rate of 80%, lower rejections of micropollutants were observed with lower water recovery rate of 60%. Except for sulfamethoxazole, the risk quotients of other detected 20 micropollutants in NF effluent were all lower than 1.0, showing medium or no risks to aquatic organisms. This study might aid understanding the performance of micropollutants rejections by NF in actual engineering application and could give guideline to the implementation of NF technology in future advanced treatment processes.

Effect of pH on Total Volume Membrane Charge Density in the Nanofiltration of Aqueous Solutions of Nitrate Salts of Heavy Metals

The separation efficiencies of aqueous solutions containing nitric salts of Zn, Cu, Fe or Pb at various pH in process of nanofiltration have been investigated experimentally. These results were used to obtain the total volume membrane charge densities, through mathematical modelling based on the Donnan-Steric partitioning Model. The experimentally obtained retention values of individual heavy metal ions varied between 36% (Zn2+ at pH = 2), 57% (Pb2+ at pH = 2), 80% (Fe3+ at pH = 9), and up to 97% (Cu2+ at pH = 9). The mathematical modelling allowed for fitting the total volume membrane charge density (Xd), which yielded values ranging from -451.90 to +900.16 mol/m3 for different non-symmetric ions. This study presents the application of nanofiltration (NF) modelling, including a consideration of each ion present in the NF system-even those originating from solutions used to adjust the pH values of the feed.

Experimental Design as a Tool for Optimizing and Predicting the Nanofiltration Performance by Treating Antibiotic-Containing Wastewater

In recent years, there has been an increase in studies regarding nanofiltration-based processes for removing antibiotics and other pharmaceutical compounds from water and wastewater. In this work, a 2^k factorial design with five control factors (antibiotic molecular weight and concentration, nanofiltration (NF) membrane, feed flow rate, and transmembrane pressure) was employed to optimize the NF performance on the treatment of antibiotic-containing wastewater. The resulting multiple linear regression model was used to predict the antibiotic rejections and permeate fluxes. Additional experiments, using the same membranes and the same antibiotics, but under different conditions of transmembrane pressure, feed flow rate, and antibiotic concentration regarding the 2^k factorial design were carried out to validate the model developed. The model was also evaluated as a tertiary treatment of urban wastewater for removing sulfamethoxazole and norfloxacin. Considering all the conditions investigated, the tightest membrane (NF97) showed higher antibiotics rejection (>97%) and lower permeate fluxes. On the contrary, the loose NF270 membrane presented lower rejections to sulfamethoxazole, the smallest antibiotic, varying from 65% to 97%, and permeate fluxes that were about three-fold higher than the NF97 membrane. The good agreement between predicted and experimental values (R² > 0.97) makes the model developed in the present work a tool to predict the NF performance when treating antibiotic-containing wastewater.