Organic matter interference with steroid hormone removal by single-walled carbon nanotubes - ultrafiltration composite membrane

A membrane fouling control strategy based on a combination of pre-treatment mitigation and in-situ membrane surface regulation using a composite coagulant

Ultrafiltration technology (UF) is efficient in surface water treatment, but its development and widespread application are limited by membrane fouling. Herein, an efficient and stable polymerized ferric titanium coagulant (PFTC) was synthesized and used as a UF pretreatment agent in actual lake water treatment. The control mechanism of PFTC on membrane fouling was investigated from the perspective of organic removal efficiency and in-situ membrane surface regulation. PFTC demonstrated a remarkable affinity for soluble metabolic intermediates and hydrophilic proteins through complexation and hydrogen bonding force, achieving removal efficiencies of 66.4 % for UV254 and 81.3 % for DOC, respectively. The hydrophilic pollutants with high molecular weight and non-saturated structure could be preferentially removed by PFTC due to its diverse hydrolysates including positively charged Fe-based hydrolysates, amorphous Ti-based hydrolysates, and highly polymerized Fe-Ti copolymers. The flocs generated by PFTC exhibited strong hydrophilicity, allowing for the formation of a loose porous cake layer on the ultrafiltration membrane, which acted as a hydrophilic layer to enhance the anti-fouling performance of ultrafiltration membrane. With its dual function of contaminant removal and in-situ membrane surface regulation, PFTC alleviated 98.9 % of membrane fouling. This study provides new insights into membrane fouling control by coagulation pretreatment and efficient treatment of surface water.

Tutorial review of error evaluation in experimental water research at the example of membrane filtration

Experimental water research lacks clear methodology to estimate experimental error. Especially when natural waters are involved, the characterization tools bear method-specific artifacts while the varying environmental conditions prevent regular repeats. This tutorial review identifies common mistakes, and proposes a practical procedure to determine experimental errors at the example of membrane filtration. Statistical analysis is often applied to an insufficient number of repeated measurements, while not all error sources and contributions are considered. This results in an underestimation of the experimental error. Variations in relevant experimental parameters need to be investigated systematically, and the related errors are quantified as a half of the variation between the max and min values when standard deviation is not applicable. Error of calculated parameters (e.g. flux, pollutant removal and mass loss) is estimated by applying error propagation, where weighing contributions of the experimental parameters are considered. Appropriate judgment and five-time repetition of a selected experiment under identical conditions are proposed to validate the propagated experimental error. For validation, the five repeated data points should lie within the estimated error range of the error bar. The proposed error evaluation procedure is adaptable in experimental water research and intended for researchers to identify the contributing factors of an experimental error and carry out appropriate error quantification and validation. The most important aim is to raise awareness of the necessity to question error methodology and reproducibility of experimental data, to produce and publish high quality research.

Removal of strontium by nanofiltration: Role of complexation and speciation of strontium with organic matter

Strontium (Sr) removal from water is required because excessive naturally occurring Sr exposure is hazardous to human health. Climate and seasonal changes cause water quality variations, in particular quality and quantity of organic matter (OM) and pH, and such variations affect Sr removal by nanofiltration (NF). The mechanisms for such variations are not clear and thus OM complexation and speciation require attention. Sr removal by NF was investigated with emphasis on the role of OM (type and concentration) and pH (2-12) on possible removal mechanisms, specifically size and/or charge exclusion as well as solute-solute interactions. The filtration results show that the addition of various OM (10 types) and an increase of OM concentration (2-100 mgC.L-1) increased Sr removal by 10-15%. The Sr-OM interaction was enhanced with increasing OM concentration, implying enhanced size exclusion via Sr-OM interaction as the main mechanism. Such interactions were quantified by asymmetric flow field-flow fractionation (FFFF) coupled with an inductively coupled plasma mass spectrometer (ICP-MS). Both extremely low and high pH increased Sr removal due to the enhanced charge exclusion and Sr-OM interactions. This work elucidated and verified the mechanism of OM and pH on Sr removal by NF membranes.

Nitrogen compounds removal from brackish water by electrodialysis at fixed electric potential and dynamic current density operations

Nitrogen (N) compounds can occur in water resources from natural and anthropogenic activities. It is ideal that these contaminants be removed before water consumption. As water quality has been affected by increased salinity and pH variation, more advanced and robust technologies such as electrodialysis (ED) can be considered for simultaneous desalination and pollutant removal. In this context, the removal of N-species (NO3-, NO2-, NH4+, and CH4N2O) from brackish water by ED was investigated for different feed water quality, considering increased salinity (0 - 10g/L NaCl) and pH variation (3 - 11), under limit current density (LCD) at fixed electric potential condition. The applied electric potential (5 - 25V) under, at, and over the LCD at fixed electric potential and dynamic current density (DCD), as a percentage of LCD (0.4 - 1.2), were analyzed to improve the process. In addition, energy efficiency in the form of specific energy consumption (SEC) and current efficiency (CE) were assessed for ED at fixed electric potential and DCD. The results showed that, at extreme pH of the feed water, the removal of NO2- and NH4+ can be affected, while NO3-was the most stable compound with pH variation. An increase in feed water salinity just slightly impacted the removal of N-compounds, due to the similar characteristics of the ions in the water. The increase in electric potential at fixed electric potential or DCD increased the removal and molar flux of N-compounds. However, operating over the LCD increased the SEC of the ED process while changes in removal were not significant. DCD procedures resulted in higher CE and shorter run time of the experiments. Therefore, ED proved to be a suitable treatment technique to produce fresh water due to the selective removal of the studied ions, especially at 15V (fixed electrical potential) and 0.8 LCD (DCD) related to removal, molar flux, and run time to achieve guidelines.

Influence of organic matter on the photocatalytic degradation of steroid hormones by TiO2-coated polyethersulfone microfiltration membrane

Water treatment in photocatalytic membrane reactors (PMR) holds great promise for removing micropollutants from aquatic environments. Organic matter (OM) that is present in any water matrix may significantly interfere with the degradation of steroid hormone (SH) micropollutants in PMRs. In this study, the interference of various OM types, humic acid (HA), Australian natural organic matter (AUS), worm farm extract (WF), tannic acid (TA), and gallic acid (GA) with the SH degradation at its environmentally relevant concentration (100 ng/L) in a flow-through PMR equipped with a polyethersulphone-titanium dioxide (PES-TiO2) membrane operated under UV light (365 nm) was investigated. Results of this study showed that OM effects are complex and depend on OM type and concentration. The removal of β-estradiol (E2) was enhanced by HA at its levels below 5 mgC/L while the enhancement was abated at higher HA concentrations. The E2 removal was inhibited by TA, and GA, while no significant interference observed for AUS, and WF. The data demonstrated diverse roles of OM that acts in PMRs as a light screening agent, a photoreactive species scavenger, an adsorption alteration trigger, and a photosensitizer. The time-resolved fluorescence measurement showed that HA, acting as a photosensitizer, promoted the sensitization of TiO2 by absorbing light energy and transferring energy/electron to the TiO2 substrate. This pathway dominated the mechanism of the enhanced E2 degradation by HA. The favorable effect of HA was augmented as increasing the light intensity from 0.5 to 10 mW/cm2 and was weakened at higher light intensities due to the increased scavenging reactions and the limited amount of HA. This work clarifies the underlying mechanism of the OM interference on photocatalytic degradation of E2 by the PES-TiO2 PMR.

Water quality of The Gambia River: A prospective drinking water supply

Drinking water in The Gambia is mostly derived from boreholes that could potentially be contaminated. The Gambia River, a major river in West Africa that covers 12 % of the country's area, could be more exploited for drinking water supply. During the dry season, the total dissolved solids (TDS), ranging from 0.02 to 33 g/L in The Gambia River, decreases with the distance to the river mouth with no major inorganic contamination. The freshwater (<0.8 g/L TDS) starts from Jasobo at approximately 120 km from the river mouth and extends by about 350 km to the eastern border of The Gambia. With a dissolved organic carbon (DOC) ranging from 2 to 15 mgC/L, the natural organic matter (NOM) of The Gambia River was characterised by 40-60 % humic substances of paedogenic origin. With such characteristics, unknown disinfection by-products could be formed if chemical disinfection, such as chlorination, was implemented during treatment. Out of 103 types of micropollutants, 21 were detected (4 pesticides, 10 pharmaceuticals, 7 per- and polyfluoroalkyl substances (PFAS)) with concentrations ranging from 0.1 to 1500 ng/L. Pesticides, bisphenol A and PFAS concentrations were below the stricter EU guidelines set for drinking water. These were mainly confined to the urban area of high population density near the river mouth, while the quality of the freshwater region of low population density was surprisingly pristine. These results indicate that The Gambia River, especially in its upper regions, would be well suited as a drinking water supply when using decentralised ultrafiltration treatment for the removal of turbidity, as well as, depending on pore size, to a certain extent microorganisms and DOC.

Poly(vinylidene fluoride) membrane with immobilized TiO2 for degradation of steroid hormone micropollutants in a photocatalytic membrane reactor

The lack of effective technologies to remove steroid hormones (SHs) from aquatic systems is a critical issue for both environment and public health. The performance of a flow-through photocatalytic membrane reactor (PMR) with TiO₂ immobilized on a photostable poly(vinylidene fluoride) membrane (PVDF-TiO₂) was evaluated in the context of SHs degradation at concentrations from 0.05 to 1000 µg/L under UV exposure (365 nm). A comprehensive investigation into the membrane preparation approach, including varying the surface Ti content and distribution, and membrane pore size, was conducted to gain insights on the rate-limiting steps for the SHs degradation. Increasing surface Ti content from 4 % to 6.5 % enhanced the 17β-estradiol (E2) degradation from 46 ± 12-81 ± 6 %. Apparent degradation kinetics were independent of both TiO₂ homogeneity and membrane pore size (0.1-0.45 µm). With optimized conditions, E2 removal was higher than 96 % at environmentally relevant feed concentration (100 ng/L), a flux of 60 L/m²h, 25 mW/cm², and 6.5 % Ti. These results indicated that the E2 degradation on the PVDF-TiO₂ membrane was limited by the catalyst content and light penetration depth. Further exploration of novel TiO₂ immobilization approach that can offer a larger catalyst content and light penetration is required to improve the micropollutant removal efficiency in PMR.

Deciphering the microheterogeneous repartition effect of environmental matrix on surface-enhanced Raman spectroscopy (SERS) analysis for pollutants in natural waters

Although surface-enhanced Raman spectroscopy (SERS) offers a promising technology for sensitive detection of environmental pollutants in natural waters, its performance can be greatly affected by the environmental matrix. The lack of identification of the origin and the underlying mechanism of matrix effect hinders the application of SERS in practical environmental analysis. Herein, with silver nanoparticles (AgNPs) as a solution-based SERS substrate, the matrix effect from environmental waters on SERS analysis and the underlying mechanisms were investigated. It was found that natural water matrix could deteriorate SERS performance and cause artefacts in SERS spectra. Among various aqueous components, natural organic matter (NOM), including humic substances and proteins, mainly contributed to the matrix effect on SERS detection, while polysaccharides or inorganic ions had minor influence. The matrix effect from NOM was found to be prevalent for different analytes and SERS substrates. The mechanism of the matrix effect from NOM in the ternary system of analyte, NOM, and nanoparticles was investigated through three mutual interactions. The microheterogeneous repartition of analytes by NOM, other than the formation of NOM-corona or competitive adsorption between NOM and analytes on nanoparticles, was found to play the dominating role in interfering with SERS detection. This work illuminates the origin and underlying mechanisms of the matrix effect, which will promote the practical application of SERS technology in environmental analysis.

Prediction of organic contaminant rejection by nanofiltration and reverse osmosis membranes using interpretable machine learning models

Efficiency improvement in contaminant removal by nanofiltration (NF) and reverse osmosis (RO) membranes is a multidimensional process involving membrane material selection and experimental condition optimization. It is unrealistic to explore the contributions of diverse influencing factors to the removal rate by trial-and-error experimentation. However, the advanced machine learning (ML) method is a powerful tool to simulate this complex decision-making process. Here, 4 traditional learning algorithms (MLR, SVM, ANN, kNN) and 4 ensemble learning algorithms (RF, GBDT, XGBoost, LightGBM) were applied to predict the removal efficiency of contaminants. Results reported here demonstrate that ensemble models showed significantly better predictive performance than traditional models. More importantly, this study achieved a compelling tradeoff between accuracy and interpretability for ensemble models with an effective model interpretation approach, which revealed the mutual interaction mechanism between the membrane material, contaminants and experimental conditions in membrane separation. Additionally, feature selection was for the first time achieved based on the aforementioned model interpretation method to determine the most important variable influencing the contaminant removal rate. Ultimately, the four ensemble models retrained by the selected variables achieved distinguished prediction performance (R²_adj = 92.4 %-99.5 %). MWCO (membrane molecular weight cut-off), McGowan volume of solute (V) and molecular weight (MW) of the compound were demonstrated to be the most important influencing factors in contaminant removal by the NF and RO processes. Overall, the proposed methods in this study can facilitate versatile complex decision-making processes in the environmental field, particularly in contaminant removal by advanced physicochemical separation processes.

Renewable energy powered membrane technology: Implications of adhesive interaction between membrane and organic matter on spontaneous osmotic backwash cleaning

Organic matter (OM) in surface and ground waters may cause membrane fouling that is laborious to clean once established. Spontaneous osmotic backwash (OB) induced by solar irradiance fluctuation has been demonstrated for early mineral scaling/organic fouling control in decentralised small-scale photovoltaic powered-nanofiltration/reverse osmosis (PV-NF/RO) membrane systems. However, various OM types will interact differently with membranes which in turn affects the effectiveness of OB. This work evaluates the suitability of spontaneous OB cleaning for eleven OM types (covering low-molecular-weight organics (LMWO), humic substances, polyphenolic compounds and biopolymers) regarding adhesive interactions with NF/RO membranes. The adhesive interactions were quantified by an asymmetric flow field-flow fractionation coupled with an organic carbon detector (FFFF-OCD). The underlying mechanism of OM-membrane adhesive interactions affecting OB cleaning was elucidated. The results indicate that humic acid (a typical humic substance) and tannic acid (a typical polyphenolic compound) induced stronger adhesive interaction with NF/RO membranes than biopolymers and LMWO. When the mass loss of an OM due to adhesion was below a critical range, the spontaneous OB is most effective (>85% flux recovery); and above this range, the OB becomes ineffective (<50% flux recovery). Polyphenolic compounds and humic substances resulted in lower OB cleaning efficiency, due to their higher aromatic content, enhancing hydrophobic interactions and hydrogen bonding. Calcium-facilitated adhesion of some OM types (such as humic substances, polyphenolics and biopolymers) increased irreversible organic fouling potential and weakened OB cleaning, which was verified by both FFFF-OCD and membrane filtration results. This work provides a guidance to formulate strategies to enhance spontaneous OB cleaning, such as first identifying the adhesion of OM in feedwater (surface and ground waters) using FFFF-OCD, and then removing "sticky" OM using suitable pre-treatment processes.

Preparation of lightweight daisy-like magnetic molecularly imprinted polymers via etching synergized template immobilization for enhanced rapid detection of trace 17β-estradiol

17β-estradiol (E2), as one of the pharmaceutical and personal care product, frequently contaminates environmental water as estrogen pollutant and possesses great risk to human survival as well as the sustainable development of the ecosystem. Herein, to achieve an effective adsorbent system for the selective removal of E2 from the environmental water, Fe₃O₄ nanoparticles are subjected to chemical etching to reduce the overall mass and then employed as carriers to prepare a novel type of lightweight daisy-like magnetic molecularly imprinted polymers (LD-MMIPs) adopting template immobilization strategy. The LD-MMIPs based etched magnetic nanoparticles not only exhibit light mass but also have plentiful imprinted sites in the etched channels, which significantly increases the adsorption capacity for E2. The daisy-like LD-MMIPs own strong magnetic responsiveness, well crystallinity, fast binding kinetics, high adsorption amount, and excellent selectivity. Moreover, combining with HPLC, the LD-MMIPs as adsorbents have been successfully used to specifically recognize and detect trace E2 in environmental water. Thus, the proposed LD-MMIPs with high adsorption capacity hold great potential in monitoring water pollution. Additionally, this work also provides an alternative strategy for improving the adsorption capacity of magnetic molecularly imprinted polymers through a convenient chemical etching technology.

Removal of arsenic(III) via nanofiltration: contribution of organic matter interactions

The removal of arsenic(III) (As(III)) with nanofiltration (NF) was investigated with emphasis on the role of salinity, pH and organic matter on retention mechanisms. While no measurable impact of salinity on As(III) retention with NF membranes (NF270 and NF90) was observed, a significant increase in As(III) retention occurred from pH 9 to pH 12. This was explained by As(III) deprotonation at pH > 9 that enhanced Donnan (charge) exclusion. Of the five different organic matter types investigated at 10 mgC/L, only humic acid (HA) increased As(III) retention by up to 10%. Increasing HA concentration to 100 mgC/L enhanced As(III) retention by 40%, which was attributed to As(III)-HA complexation. Complexation was confirmed by field-flow fractionation inductively coupled plasma mass spectrometry (FFF-ICP-MS) measurements, which showed that the bound As(III) increased with HA concentration. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) showed that NF90, which exhibited lower permeability reduction than NF270, has accumulated a lower amount of As(III) in the presence of HA, where As(III)-HA complex was formed in the feed solution. This finding implies that As(III) retention with NF technology can be enhanced by complexation, instead of using other methods such as oxidation or pH adjustement.