Electrocatalytic reduction of nitrate using Pd-Cu modified carbon nanotube membranes

● Pd-Cu modified CNT membranes were prepared successfully by electrodeposition method. ● The deposition voltage and deposition time were optimized for Pd-Cu co-deposition. ● NO₃⁻-N was removed efficiently from water by Pd-Cu modified CNT membranes. ● The presence of dissolved oxygen did not affect the nitrate reduction performance. ● Mass transfer rate was promoted significantly with the increase in membrane flux. Excessive nitrate in water is harmful to the ecological environment and human health. Electrocatalytic reduction is a promising technology for nitrate removal. Herein, a Pd-Cu modified carbon nanotube membrane was fabricated with an electrodeposition method and used to reduce nitrate in a flow-through electrochemical reactor. The optimal potential and duration for codeposition of Pd and Cu were −0.7 V and 5 min, respectively, according to linear scan voltammetry results. The membrane obtained with a Pd:Cu ratio of 1:1 exhibited a relatively high nitrate removal efficiency and N₂ selectivity. Nitrate was almost completely reduced (~99 %) by the membrane at potentials lower than −1.2 V. However, −0.8 V was the optimal potential for nitrate reduction in terms of both nitrate removal efficiency and product selectivity. The nitrate removal efficiency was 56.2 %, and the N₂ selectivity was 23.8 % for the Pd:Cu=1:1 membrane operated at −0.8 V. Nitrate removal was enhanced under acidic conditions, while N₂ selectivity was decreased. The concentrations of Cl⁻ ions and dissolved oxygen showed little effect on nitrate reduction. The mass transfer rate constant was greatly improved by 6.6 times from 1.14 × 10⁻³ m/h at a membrane flux of 1 L/(m²·h) to 8.71 × 10⁻³ m/h at a membrane flux of 15 L/(m²·h), which resulted in a significant increase in the nitrate removal rate from 13.6 to 133.5 mg/(m²·h). These findings show that the Pd-Cu modified CNT membrane is an efficient material for nitrate reduction.     

Nonpolar cross-stacked super-aligned carbon nanotube membrane for efficient wastewater treatment

● A novel nonpolar super-aligned carbon nanotube (SACNT) membrane was prepared. ● SACNT membranes achieved smoother and more uniform structures. ● SACNT membranes have inert chemistry and unique nonpolar wetting feature. ● SACNT membranes exhibit superior separation and antifouling capabilities. ● SACNT membranes achieved superior oil/water separation efficiency. Membrane separation technology has made great progress in various practical applications, but the unsatisfactory separation performance of prevailing membrane materials hampers its further sustainable growth. This study proposed a novel nonpolar super-aligned carbon nanotube (SACNT) membrane, which was prepared with a layer-by-layer cross-stacking method. Through controlling the number of stacked SACNT layers, three kinds of SACNT membranes (SACNT_200, SACNT_300, and SACNT_400) were prepared. Systematic characterizations and filtration tests were performed to investigate their physico-chemical properties, surface wetting behavior, and filtration performance. Compared with two commercial membranes (Com_0.22 and Com_0.45), all the SACNT membranes achieved smoother and more uniform structures. Due to the hexagonal graphene structure of CNTs, the surface chemistry of the SACNT membranes is simple and inert, thereby potentially eliminating the covalent-bonding-induced membrane fouling. Besides, the SACNT membranes exhibited a typical nonpolar wetting behavior, with high contact angles for polar liquids (water: ~124.9°–126.5°; formamide: ~80.0°–83.9°) but low contact angles for nonpolar diiodomethane (~18.8°–20.9°). This unique nonpolar feature potentially leads to weak interactions with polar substances. Furthermore, compared with the commercial membranes, the SACNT membranes obtained a significantly higher selectivity while achieving a comparable or higher permeability (depending on the number of stacked layers). Moreover, the SACNT membranes exhibited superior separation performance in various application scenarios, including municipal wastewater treatment (> 2.3 times higher cleaning efficiency), electro-assistant fouling inhibition (or even self-cleaning), and oil/water separation (> 99.2 % of separation efficiency), suggesting promising application prospects in various fields.     

Efficient production of hydrogen peroxide in microbial reverse-electrodialysis cells coupled with thermolytic solutions

● Appreciable H₂O₂ production rate was achieved in MRCs utilizing NH₄HCO₃ solutions. ● Carbon black outperformed activated carbon as the catalyst for H₂O₂ production. ● The optimum carbon black loading for H₂O₂ production on air-cathode was 10 mg/cm². ● The optimum number of cell pairs was determined to be three. ● A maximum power density of 980 mW/m² was produced by MRCs with 5 cell pairs. H₂O₂ was produced at an appreciable rate in microbial reverse-electrodialysis cells (MRCs) coupled with thermolytic solutions, which can simultaneously capture waste heat as electrical energy. To determine the optimal cathode and membrane stack configurations for H₂O₂ production, different catalysts, catalyst loadings and numbers of membrane cell pairs were tested. Carbon black (CB) outperformed activated carbon (AC) for H₂O₂ production, although AC showed higher catalytic activity for oxygen reduction. The optimum CB loading was 10 mg/cm² in terms of both the H₂O₂ production rate and power production. The optimum number of cell pairs was determined to be three based on a tradeoff between H₂O₂ production and capital costs. A H₂O₂ production rate as high as 0.99 ± 0.10 mmol/(L·h) was achieved with 10 mg/cm² CB loading and 3 cell pairs, where the H₂O₂ recovery efficiency was 52 ± 2% and the maximum power density was 780 ± 37 mW/m². Increasing the number of cell pairs to five resulted in an increase in maximum power density (980 ± 21 mW/m²) but showed limited effects on H₂O₂ production. These results indicated that MRCs can be an efficient method for sustainable H₂O₂ production.     

Insights into the electron transfer mechanisms of permanganate activation by carbon nanotube membrane for enhanced micropollutants degradation

● A CNT filter enabled effective KMnO₄ activation via facilitated electron transfer. ● Ultra-fast degradation of micropollutants were achieved in KMnO₄/CNT system. ● CNT mediated electron transfer process from electron-rich molecules to KMnO₄. ● Electron transfer dominated organic degradation. Numerous reagents have been proposed as electron sacrificers to induce the decomposition of permanganate (KMnO₄) by producing highly reactive Mn species for micropollutants degradation. However, this strategy can lead to low KMnO₄ utilization efficiency due to limitations associated with poor mass transport and high energy consumption. In the present study, we rationally designed a catalytic carbon nanotube (CNT) membrane for KMnO₄ activation toward enhanced degradation of micropollutants. The proposed flow-through system outperformed conventional batch reactor owing to the improved mass transfer via convection. Under optimal conditionals, a > 70% removal (equivalent to an oxidation flux of 2.43 mmol/(h·m²)) of 80 μmol/L sulfamethoxazole (SMX) solution can be achieved at single-pass mode. The experimental analysis and DFT studies verified that CNT could mediate direct electron transfer from organic molecules to KMnO₄, resulting in a high utilization efficiency of KMnO₄. Furthermore, the KMnO₄/CNT system had outstanding reusability and CNT could maintain a long-lasting reactivity, which served as a green strategy for the remediation of micropollutants in a sustainable manner. This study provides new insights into the electron transfer mechanisms and unveils the advantages of effective KMnO₄ utilization in the KMnO₄/CNT system for environmental remediation.     

Ceramic membrane fouling mechanisms and control for water treatment

● The fouling is summarized based on ceramic membrane performance and pollutants. ● The current research methods and theoretical models are summarized. ● The membrane fouling control methods and collaborative technology are reviewed. Membrane separation, as an important drinking water treatment technology, has wide applications. The remarkable advantages of ceramic membranes, such as chemical stability, thermal stability, and high mechanical strength, endow them with broader prospects for development. Despite the importance and advantages of membrane separation in water treatment, the technique has a limitation: membrane fouling, which greatly lowers its effectiveness. This is caused by organics, inorganic substances, and microorganisms clogging the pore and polluting the membrane surface. The increase in membrane pollution greatly lowers purification effectiveness. Controlling membrane fouling is critical in ensuring the efficient and stable operation of ceramic membranes for water treatment. This review analyzes four mechanisms of ceramic membrane fouling, namely complete blocking, standard blocking, intermediate blocking, and cake filtration blocking. It evaluates the mechanisms underlying ceramic membrane fouling and summarizes the progress in approaches aimed at controlling it. These include ceramic membrane pretreatment, ceramic membrane surface modification, membrane cleaning, magnetization, ultrasonics, and nanobubbles. This review highlights the importance of optimizing ceramic membrane preparation through further research on membrane fouling and pre-membrane pretreatment mechanisms. In addition, combining process regulations with ceramic membranes as the core is an important research direction for ceramic membrane-based water treatment.     

Distribution,enrichment mechanism and risk assessment for fluoride in groundwater: a case study of Mihe-Weihe River Basin,China

● High fluorine is mainly HCO₃·Cl-Na and HCO₃-Na type. ● F⁻ decreases with the increase of depth to water table. ● High fluoride is mainly affected by fluorine-containing minerals and weak alkaline. ● Fluorine pollution is mainly in the north near Laizhou Bay (wet season > dry season). ● Groundwater samples have a high F⁻ health risk (children > adults). Due to the unclear distribution characteristics and causes of fluoride in groundwater of Mihe-Weihe River Basin (China), there is a higher risk for the future development and utilization of groundwater. Therefore, based on the systematic sampling and analysis, the distribution features and enrichment mechanism for fluoride in groundwater were studied by the graphic method, hydrogeochemical modeling, the proportionality factor between conventional ions and factor analysis. The results show that the fluorine content in groundwater is generally on the high side, with a large area of medium-fluorine water (0.5–1.0 mg/L), and high-fluorine water is chiefly in the interfluvial lowlands and alluvial-marine plain, which mainly contains HCO₃·Cl-Na- and HCO₃-Na-type water. The vertical zonation characteristics of the fluorine content decrease with increasing depth to the water table. The high flouride groundwater during the wet season is chiefly controlled by the weathering and dissolution of fluorine-containing minerals, as well as the influence of rock weathering, evaporation and concentration. The weak alkaline environment that is rich in sodium and poor in calcium during the dry season is the main reason for the enrichment of fluorine. Finally, an integrated assessment model is established using rough set theory and an improved matter element extension model, and the level of groundwater pollution caused by fluoride in the Mihe-Weihe River Basin during the wet and dry seasons in the Shandong Peninsula is defined to show the necessity for local management measures to reduce the potential risks caused by groundwater quality.     

Construction of MOFs-based nanocomposite membranes for emerging organic contaminants abatement in water

● Application of the MOF-composite membranes in adsorption was discussed. ● Recent application of MOFs-membranes for separation was summarized. ● Separation and degradation for emerging organic contaminants were described. Presence of emerging organic contaminants (EOCs) in water is one of the major threats to water safety. In recent decades, an increasing number of studies have investigated new approaches for their effective removal. Among them, metal-organic frameworks (MOFs) have attracted increasing attention since their first development thanks to their tunable metal nodes and versatile, functional linkers. However, whether or not MOFs have a promising future for practical application in emerging contaminants-containing wastewater is debatable. This review summarizes recent studies about the removal of EOCs using MOFs-related material. The synthesis strategies of both MOF particles and composites, including thin-film nanocomposite and mixed matrix membranes, are critically reviewed, as well as various characterization technologies. The application of the MOF-based composite membranes in adsorption, separation (nanofiltration and ultrafiltration), and catalytic degradation are discussed. Overall, literature survey shows that MOFs-based composite could play a crucial role in eliminating EOCs in the future. In particular, modified membranes that realize separation and degradation might be the most promising materials for such application.     

Recent advances in electrochemical decontamination of perfluorinated compounds from water: a review

● Recent advances in the electrochemical decontamination of PFAS are reviewed. ● Underlying mechanisms and impacting factors of these processes are discussed. ● Several novel couped systems and electrode materials are emphasized. ● Major knowledge gaps and research prospects on PFAS removal are identified. Per- and polyfluoroalkyl substances (PFAS) pose serious human health and environmental risks due to their persistence and toxicity. Among the available PFAS remediation options, the electrochemical approach is promising with better control. In this review, recent advances in the decontamination of PFAS from water using several state-of-the-art electrochemical strategies, including electro-oxidation, electro-adsorption, and electro-coagulation, were systematically reviewed. We aimed to elucidate their design principles, underlying working mechanisms, and the effects of operation factors (e.g., solution pH, applied voltage, and reactor configuration). The recent developments of innovative electrochemical systems and novel electrode materials were highlighted. In addition, the development of coupled processes that could overcome the shortcomings of low efficiency and high energy consumption of conventional electrochemical systems was also emphasized. This review identified several major knowledge gaps and challenges in the scalability and adaptability of efficient electrochemical systems for PFAS remediation. Materials science and system design developments are forging a path toward sustainable treatment of PFAS-contaminated water through electrochemical technologies.     

Modelling the thresholds of nitrogen/phosphorus concentration and hydraulic retention time for bloom control in reclaimed water landscape

● A new model for bloom control in open land scape water was constructed. ● It considers the effects of temperature and light on algae growth. ● It describes threshold curve of nitrogen, phosp horus and hydraulic retention time. ● Light and temperature dependent growth para meters of typical algae were obtained. The risks posed by algal blooms caused by nitrogen and phosphorus in reclaimed water used in urban water landscapes need to be carefully controlled. In this study, the combined effects of the nitrogen and phosphorus concentrations and the light intensity and temperature on the specific growth rates of algae were determined using Monod, Steele, and Arrhenius models, then an integrated algal growth model was developed. The algae biomass, nitrogen concentration, and phosphorus concentration mass balance equations were used to establish a new control model describing the nitrogen and phosphorus concentration and hydraulic retention time thresholds for algal blooms. The model parameters were determined by fitting the models to data acquired experimentally. Finally, the control model and numerical simulations for six typical algae and mixed algae under standard conditions were used to determine nitrogen/phosphorus concentration and hydraulic retention time thresholds for landscape water to which reclaimed water is supplied (i.e., for a reclaimed water landscape).     

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov chain Monte Carlo algorithm

● A hydrodynamic-Bayesian inference model was developed for water pollution tracking. ● Model is not stuck in local optimal solutions for high-dimensional problem. ● Model can estimate source parameters accurately with known river water levels. ● Both sudden spill incident and normal sewage inputs into the river can be tracked. ● Model is superior to the traditional approaches based on the test cases. Water quality restoration in rivers requires identification of the locations and discharges of pollution sources, and a reliable mathematical model to accomplish this identification is essential. In this paper, an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge. The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method (MCMC). The methodological framework is tested using a designed case of a sudden wastewater spill incident (i.e., source location, flow rate, and starting and ending times of the discharge) and a real case of multiple sewage inputs into a river (i.e., locations and daily flows of sewage sources). The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites. It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space. In comparison, the inverse models based on the popular random walk Metropolis (RWM) algorithm and microbial genetic algorithm (MGA) do not produce reliable estimates for the two scenarios even after multiple simulation runs, and they fall into locally optimal solutions. Since much more water level data are available than water quality data, the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data, especially for rivers receiving significant sewage discharges.     

Revealing the GHG reduction potential of emerging biomass-based CO2 utilization with an iron cycle system

● Greenhouse gas mitigation by biomass-based CO₂ utilization with a Fe cycle system. ● The system including hydrothermal CO₂ reduction with Fe and Fe recovery by biomass. ● The reduction potential quantified by experiments, simulations, and an ex-ante LCA. ● The greatest GHG reduction potential is −34.03 kg CO₂-eq/kg absorbed CO₂. ● Ex-ante LCA supports process optimization to maximize GHG reduction potential. CO₂ utilization becomes a promising solution for reducing anthropogenic greenhouse gas (GHG) emissions. Biomass-based CO₂ utilization (BCU) even has the potential to generate negative emissions, but the corresponding quantitative evaluation is limited. Herein, the biomass-based CO₂ utilization with an iron cycle (BCU-Fe) system, which converts CO₂ into formate by Fe under hydrothermal conditions and recovers Fe with biomass-derived glycerin, was investigated. The GHG reduction potential under various process designs was quantified by a multidisciplinary method, including experiments, simulations, and an ex-ante life-cycle assessment. The results reveal that the BCU-Fe system could bring considerable GHG emission reduction. Significantly, the lowest value is −34.03 kg CO₂-eq/kg absorbed CO₂ (−2.44 kg CO₂-eq/kg circulated Fe) with the optimal yield of formate (66%) and Fe (80%). The proposed ex-ante evaluation approach not only reveals the benefits of mitigating climate change by applying the BCU-Fe system, but also serves as a generic tool to guide the industrialization of emerging carbon-neutral technologies.     

Mitigating microbiological risks of potential pathogens carrying antibiotic resistance genes and virulence factors in receiving rivers: Benefits of wastewater treatment plant upgrade

● Abundance of MAGs carrying ARG-VF pairs unchanged in rivers after WWTP upgrade. ● Upgrade of WWTPs significantly reduced diversity of pathogenic genera in rivers. ● Upgrade of WWTPs reduced most VF (ARG) types carried by potential pathogens in rivers. ● Upgrade of WWTPs narrowed the pathogenic host ranges of ARGs and VFs in rivers. Wastewater treatment plants (WWTPs) with additional tertiary ultrafiltration membranes and ozonation treatment can improve water quality in receiving rivers. However, the impacts of WWTP upgrade (WWTP-UP) on pathogens carrying antibiotic resistance genes (ARGs) and virulence factors (VFs) in rivers remain poorly understood. In this study, ARGs, VFs, and their pathogenic hosts were investigated in three rivers impacted by large-scale WWTP-UP. A five-year sampling campaign covered the periods before and after WWTP-UP. Results showed that the abundance of total metagenome-assembled genomes (MAGs) containing both ARGs and VFs in receiving rivers did not decrease substantially after WWTP-UP, but the abundance of MAGs belonging to pathogenic genera that contain both ARGs and VFs (abbreviated as PAVs) declined markedly. Genome-resolved metagenomics further revealed that WWTP-UP not only reduced most types of VFs and ARGs in PAVs, but also effectively eliminated efflux pump and nutritional VFs carried by PAVs in receiving rivers. WWTP-UP narrowed the pathogenic host ranges of ARGs and VFs and mitigated the co-occurrence of ARGs and VFs in receiving rivers. These findings underline the importance of WWTP-UP for the alleviation of pathogens containing both ARGs and VFs in receiving rivers.     

Electroreduction of hexavalent chromium using a porous titanium flow-through electrode and intelligent prediction based on a back propagation neural network

● Titanium-based flow-through electrode achieved high Cr(VI) reduction efficiency. ● Flow-through pattern enhanced the mass transfer and reduced cathodic polarization. ● BPNN predicted the optimal electroreduction conditions of flow-through cell. Flow-through electrodes have been demonstrated to be effective for electroreduction of Cr(VI), but shortcomings are tedious preparation and short lifetimes. Herein, porous titanium available in the market was studied as a flow-through electrode for Cr(VI) electroreduction. In addition, the intelligent prediction of electrolytic performance based on a back propagation neural network (BPNN) was developed. Voltametric studies revealed that Cr(VI) electroreduction was a diffusion-controlled process. Use of the flow-through mode achieved a high limiting diffusion current as a result of enhanced mass transfer and favorable kinetics. Electroreduction of Cr(VI) in the flow-through system was 1.95 times higher than in a parallel-plate electrode system. When the influent (initial pH 2.0 and 106 mg/L Cr(VI)) was treated at 5.0 V and a flux of 51 L/(h·m²), a reduction efficiency of ~99.9% was obtained without cyclic electrolysis process. Sulfate served as the supporting electrolyte and pH regulator, as reactive CrSO₇²⁻ species were formed as a result of feeding HSO₄⁻. Cr(III) was confirmed as the final product due to the sequential three-electron transport or disproportionation of the intermediate. The developed BPNN model achieved good prediction accuracy with respect to Cr(VI) electroreduction with a high correlation coefficient (R² = 0.943). Additionally, the electroreduction efficiencies for various operating inputs were predicted based on the BPNN model, which demonstrates the evolutionary role of intelligent systems in future electrochemical technologies.     

Predicting the elemental compositions of solid waste using ATR-FTIR and machine learning

● A method based on ATR-FTIR and ML was developed to predict CHNS contents in waste. ● Feature selection methods were used to improve models’ prediction accuracy. ● The best model predicted C, H, and N contents with accuracy R ² ≥ 0.93, 0.87, 0.97. ● Some suitable models showed insensitivity to spectral noise. ● Under moisture interference, the models still had good prediction performance. Elemental composition is a key parameter in solid waste treatment and disposal. This study has proposed a method based on infrared spectroscopy and machine learning algorithms that can rapidly predict the elemental composition (C, H, N, S) of solid waste. Both noise and moisture spectral interference that may occur in practical application are investigated. By comparing two feature selection methods and five machine learning algorithms, the most suitable models are selected. Moreover, the impacts of noise and moisture on the models are discussed, with paper, plastic, textiles, wood, and leather as examples of recyclable waste components. The results show that the combination of the feature selection and K-nearest neighbor (KNN) approaches exhibits the best prediction performance and generalization ability. Particularly, the coefficient of determination (R²) of the validation set, cross validation and test set are higher than 0.93, 0.89, and 0.97 for predicting the C, H, and N contents, respectively. Further, KNN is less sensitive to noise. Under moisture interference, the combination of feature selection and support vector regression or partial least-squares regression shows satisfactory results. Therefore, the elemental compositions of solid waste are quickly and accurately predicted under noise and moisture disturbances using infrared spectroscopy and machine learning algorithms.     

Porous silica synthesis out of coal fly ash with no residue generation and complete silicon separation

● Both amorphous and crystalline silicon are completely separated from coal fly ash. ● Porous silica is synthesized out of coal fly ash. ● No residues is produced during the whole synthesis process. ● The one-step method to synthesize silica don’t need long-time reaction and aging. Ordered mesoporous silica materials exhibit enormous potential in industrial production. Since coal fly ash (CFA) is abundant in Si, it has become a green and promising way to utilize CFA by synthesizing porous silica materials. However, the stable crystalline structure of CFA limits the extraction of Si, and the residue is generated during the process of extracting Si. In this work, we proposed a no-residue method to synthesize ordered mesoporous silica out of CFA. Sodium carbonate (Na₂CO₃) was used to reconstruct the crystals of the CFA, and the calcined mixture then directly reacted with the precipitators. This method combined the process of Si extraction and porous material synthesis. In this method, no residue was generated and the silicon in both amorphous and crystalline phases of CFA was fully utilized. By this method, the extraction efficiency of Si was increased from 31.75% to nearly 100%. The as-synthesized mesoporous silica had a highly-ordered pore structure with a space group of la-3d, a surface area of 663.87 m²/g, a pore volume of 0.41 cm³/g, and an average pore diameter of 2.73 nm. The mechanism of crystalline transformation and material structure formation were systematically studied. This method provides a new idea to dispose of CFA and synthesize porous silica materials.     

Effectiveness of tertiary treatment processes in removing different classes of emerging contaminants from domestic wastewater

● Different advanced treatment processes were tested for ECs removal from wastewater. ● UV radiation showed low to moderate removal for 5 of the 38 micropollutants. ● Among tested membrane processes, nanofiltration showed the better performance. ● The use of PAC achieved high or partially removal for 31 out of the 38 compounds. ● The environmental and economical evaluation of a pilot-scale PAC unit is suggested. In this work, 38 different organic emerging contaminants (ECs), belonging to various chemical classes such as pharmaceuticals (PhCs), endocrine-disrupting chemicals (EDCs), benzotriazoles (BTRs), benzothiazoles (BTHs), and perfluorinated compounds (PFCs), were initially identified and quantified in the biologically treated wastewater collected from Athens’ (Greece) Sewage Treatment Plant (STP). Processes already used in existing STPs such as microfiltration (MF), nanofiltration (NF), ultrafiltration (UF), UV radiation, and powdered activated carbon (PAC) were assessed for ECs’ removal, under the conditions that represent their actual application for disinfection or advanced wastewater treatment. The results indicated that MF removed only one out of the 38 ECs and hence it was selected as pretreatment step for the other processes. UV radiation in the studied conditions showed low to moderate removal for 5 out of the 38 ECs. NF showed better results than UF due to the smaller pore sizes of the filtration system. However, this enhancement was observed mainly for 8 compounds originating from the classes of PhCs and PFCs, while the removal of EDCs was not statistically significant. Among the various studied technologies, PAC stands out due to its capability to sufficiently remove most ECs. In particular, removal rates higher than 70% were observed for 9 compounds, 22 were partially removed, while 7 demonstrated low removal rates. Based on our screening experiments, future research should focus on scaling-up PAC in actual conditions, combining PAC with other processes, and conduct a complete economic and environmental assessment of the treatment.     

Photo-induced surface frustrated Lewis pairs for promoted photocatalytic decomposition of perfluorooctanoic acid

● Terminal carboxylate group activation is PFOA degradation’s rate-limiting step. ● Bi₃O(OH)(PO₄)₂ with surface frustrated Lewis pairs (SFLPs) efficiently degrade PFOA. ● Photo-induced Lewis acidic sites and proximal surface hydroxyls constitute SFLPs. ● SFLPs act as collection centers to effectively adsorb PFOA. ● SFLPs endow accessible pathways for photogenerated holes rapid transfer to PFOA. Heterogeneous photocatalysis has gained substantial research interest in treating per- and polyfluoroalkyl substances (PFAS)-contaminated water. However, sluggish degradation kinetics and low defluorination efficiency compromise their practical applications. Here, we report a superior photocatalyst, defected Bi₃O(OH)(PO₄)₂, which could effectively degrade typical PFAS, perfluorooctanoic acid (PFOA), with high defluorination efficiency. The UV light irradiation could in situ generate oxygen vacancies on Bi₃O(OH)(PO₄)₂ through oxidation of the lattice hydroxyls, which further promotes the formation of Lewis acidic coordinately unsaturated bismuth sites. Then, the Lewis acidic sites couple with the proximal surface hydroxyls to constitute the surface frustrated Lewis pairs (SFLPs). With the in-depth spectroscopic analysis, we revealed that the photo-induced SFLPs act as collection centers to effectively adsorb PFOA and endow accessible pathways to transfer photogenerated holes to PFOA rapidly. Consequently, activation of the terminal carboxyl, a rate-limiting step for PFOA decomposition, could be easily achieved over the defected Bi₃O(OH)(PO₄)₂ photocatalyst. These results suggest that SFLPs exhibit great potential in developing highly efficient photocatalysts to degrade persistent organic pollutants.     

Same stimuli,different responses: a pilot study assessing air pollution visibility impacts on emotional well-being in a controlled environment

● Emotional responses to visibility-reducing haze was assessed in a controlled lab. ● Valence and arousal have non-linear responses to pollution-caused low visibility. ● Repetitive exposure aggravates negative emotions in severely polluted conditions. ● Emotional bias to pollution relates with gender, decisiveness, attitude to clean air. A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing. However, evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment. Herein, we designed a lab-based experiment (41 subjects, 6 blocks) where participants were presented with real-scene images of 12 different PM_2.5 concentrations in each block. Emotional valence (negative to positive) and arousal (calm to excited) were self-rated by participants per image, and the response time for each rating was recorded. We find that as pollution level increases from 10 to 260 µg/m³, valence scores decrease, whereas arousal scores decline first and then bounce back, following a U-shaped trend. When air quality deteriorates, individual variability decreases in hedonic valence but increases in arousal. Over blocks, repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions (> 150 µg/m³). Finally, we find females, people who are slow in making responses, and those who are highly aroused by clean air tend to express more negative responses (so-called negativity bias) to ambient pollution than their respective counterparts. These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment. Although the findings in our pilot study should only be directly applied to the conditions assessed herein, we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.     

Functional flax fiber with UV-induced switchable wettability for multipurpose oil-water separation

● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment.     

Fluorescence detection of phosphate in an aqueous environment by an aluminum-based metal-organic framework with amido functionalized ligands

● A novel Al-MOF was successfully synthesized by a facile solvothermal method. ● Al-MOF showed superior performance for phosphate detection. ● High selectivity and anti-interference for detection were demonstrated. ● The high coordination between Al-O and PO₄³⁻ was the key in fluorescence sensing. The on-site monitoring of phosphate is important for environmental management. Conventional phosphate detection methods are not appropriate to on-site monitoring owing to the use of complicated detection procedures, and the consequent high cost and maintenance requirements of the detection apparatus. Here, a highly sensitive fluorescence-based method for phosphate detection with a wide detection range was developed based on a luminescent aluminum-based metal-organic framework (Al-MOF). The Al-MOF was prepared by introducing amine functional groups to conventional MIL to enhance phosphate binding, and exhibited excellent fluorescence properties that originated from the ligand-to-metal charge transfer (LMCT). The detection limit was as low as 3.25 μmol/L (0.10 mg/L) and the detection range was as wide as 3–350 μmol/L (0.10–10.85 mg/L). Moreover, Al-MOF displayed specific recognition toward phosphate over most anions and metal cations, even for a high concentration of the co-existent ions. The mechanism of phosphate detection was analyzed through the characterization of the combination of Al-MOF and phosphate, and the results indicated the high affinity between Al-O and phosphate inhibited that the LMCT process and recovered the intrinsic fluorescence of NH₂-H₂BDC. The recovery of the developed detection method reached a satisfactory range of 85.1%–111.0%, and the feasibility of on-site phosphate detection was verified using a prototype sensor for tap water and lake water samples. It was demonstrated that the prepared Al-MOF is highly promising for on-site detection of phosphate in an aqueous environment.