Microplastics in municipal wastewater treatment plants: a case study of Denizli/Turkey

● High amounts of microplastics are released to receiving media from WWTPs. ● The effect of classical treatment processes on MP removal is important. ● MP load in the effluent of WWTPs is important for developing treatment technology. ● Additional physical treatment could help further reduce MP discharge. Plastic particles smaller than 5 mm are microplastics. They are among the significant pollutants that recently attracted attention. Great quantities of microplastics enter the sewage system daily and reach wastewater treatment plants (WWTPs). As a result, WWTPs are potential microplastic sources. Hence, they create a pathway for microplastics to reach aquatic environments with treated wastewater discharge. Studies on microplastic characterization in WWTPs have gained momentum in academia. This study investigates the abundance, size, shape, color, polymer type, and removal efficiencies of microplastics in a municipal wastewater treatment plant (WWTP) in Denizli/Turkey. The results showed that the dominant microplastic shape in wastewater samples was fibers (41.78%–60.77%) in the 100–500 µm (58.57%–80.07%) size range. Most of the microplastics were transparent-white (32.86%–58.93%). The dominant polymer types were polyethylene (54.05%) and polyethylene vinyl acetate (37.84%) in raw wastewater. Furthermore, the microplastic removal efficiencies of the Denizli Central WWTP as a whole and for individual treatment units were evaluated. Although the microplastic pollution removal efficiency of the Denizli Central WWTP was over 95%, the microplastic concentration discharged daily into the receiving environment was considerably high (1.28 × 10¹⁰ MP/d). Thus, Denizli Central WWTP effluents result in a high volume of emissions in terms of microplastic pollution with a significant daily discharge to the Çürüksu Stream.     

V-shaped substrate for surface and volume enhanced Raman spectroscopic analysis of microplastics

● V-shaped substrate was obtained for SERS analysis of microplastics (diameter ≈ 1 μm). ● Enhancement factor of V-shaped substrate can reach 20 in microplastics detection. ● V-shaped nanopore array can bring additional volume enhancement. ● V-shaped substrate was more economic in application compared to Klarite substrate. Research on the microplastics (MPs) is developing towards smaller size, but corresponding methods for the rapid and accurate detection of microplastics, especially nanoplastics still present challenge. In this work, a novel surface and volume enhanced Raman spectroscopy substrate was developed for the rapid detection of microplastic particles below 5 μm. The gold nanoparticles (NPs) were deposited onto the surface and into the V-shaped nanopores of anodized aluminum oxide (AAO) through magnetron sputtering or ion sputtering, and then AuNPs@V-shaped AAO SERS substrate was obtained and studied for microplastic detection. SERS performance of AuNPs@V-shaped AAO SERS substrate was evaluated through the detection of polystyrene and polymethyl methacrylate microspheres. Results indicated that individual polystyrene sphere with a diameter of 1 μm can be well detected on AuNPs@V-shaped AAO SERS substrate, and the maximum enhancement factor (EF) can reach 20. In addition, microplastics in ambient atmospheric samples were collected and tested to verify the effectiveness of the AuNPs@V-shaped AAO SERS substrate in the real environment. This study provides a rapid, economic and simple method for detecting and identifying microplastics with small size.     

Prediction of high-density polyethylene pyrolysis using kinetic parameters based on thermogravimetric and artificial neural networks

● Reducting the sampling frequency can enhance the modelling process. ● The pyrolysis of HDPE was investigated at three different heating rates. ● The average E_a and k₀ were calculated by Friedman, KAS, FWO, and CR methods. ● ANN was employed to predict the HDPE weight loss with the optimal MSE and R². Pyrolysis is considered an attractive option and a promising way to dispose waste plastics. The thermogravimetric experiments of high-density polyethylene (HDPE) were conducted from 105 °C to 900 °C at different heating rates (10 °C/min, 20 °C/min, and 30 °C/min) to investigate their thermal pyrolysis behavior. We investigated four methods including three model-free methods and one model-fitting method to estimate dynamic parameters. Additionally, an artificial neural network model was developed by providing the heating rates and temperatures to predict the weight loss (wt.%) of HDPE, and optimized via assessing mean squared error and determination coefficient on the test set. The optimal MSE (2.6297 × 10⁻²) and R² value (R² > 0.999) were obtained. Activation energy and pre-exponential factor obtained from four different models achieves the acceptable value between experimental and predicted results. The relative error of the model increased from 2.4 % to 6.8 % when the sampling frequency changed from 50 s to 60 s, but showed no significant difference when the sampling frequency was below 50 s. This result provides a promising approach to simplify the further modelling work and to reduce the required data storage space. This study revealed the possibility of simulating the HDPE pyrolysis process via machine learning with no significant accuracy loss of the kinetic parameters. It is hoped that this work could potentially benefit to the development of pyrolysis process modelling of HDPE and the other plastics.     

On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies

● We evaluated the accuracy of iPhone data in capturing time-activity patterns. ● iPhone data captured the most important microenvironments and time spent in them. ● iPhone data also accurately captured daily exposure to ambient PM pollution. ● A considerable fraction of the population in the USA may have iPhone data available. ● iPhone data has great potential in air pollution health studies. In many air pollution health studies, the time-activity pattern of individuals is often ignored largely due to lack of data. However, a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation. Here, we showcase the potential of iPhone’s Significant Location (iSL) data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants. In this study, one subject carried an iPhone in tandem with a reference GPS tracking device for one month. The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently. Using GPS data as a reference, we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period. We found the iSL data accurately captured the time the subject spent in 16 microenvironments (i.e. locations the subject visited more than once), which was 93% of the time during the study period. The average error of time-weighted aerosol optical depth value, a surrogate of particle pollution, is only 0.012%. To explore the availability of iSL data among iPhone users, an online survey was conducted. Among the 349 surveyed participants, 72% of them have iSL data available. Considering the popularity of iPhones, iSL data may be available for a significant portion of the general population. Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation.     

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.     

Biodegradation of waste refrigerator polyurethane by mealworms

● Waste refrigerator polyurethane (WRPU) was ingested and biodegraded by mealworms. ● The carbon in WRPU-based frass was lower than that in WRPU. ● Urethane groups in WRPU were broken down after ingestion by mealworms. ● Thermal stability of WRPU-based frass were deteriorated compared to that of WRPU. ● Gut microbiomes of mealworms fed using WRPU were distinct from that fed using bran. Refrigerator insulation replacement results in discarding a large amount of waste refrigerator polyurethane (WRPU). Insect larvae like mealworms have been used to biodegrade pristine plastics. However, knowledge about mealworms degrading WRPU is scarce. This study presents an in-depth investigation of the degradation of WRPU by mealworms using the micro-morphology, composition, and functional groups of WRPU and the egested frass characteristics. It was found that the WRPU debris in frass was scoured, implying that WRPU was ingested and degraded by mealworms. The carbon content of WRPU-based frass was lower than that of WRPU, indicating that mealworms utilized WRPU as a carbon source. The urethane groups in WRPU were broken, and benzene rings’ C=C and C–H bonds in the isocyanate disappeared after being ingested by mealworms. Thermal gravimetric-differential thermal gravimetry analysis showed that the weight loss temperature of WRPU-based frass was 300 °C lower than that of WRPU, indicating that the thermal stability of WRPU deteriorated after being ingested. The carbon balance analysis confirmed that carbon in the ingested WRPU released as CO₂ increased from 18.84 % to 29.80 %, suggesting that WRPU was partially mineralized. The carbon in the mealworm biomass ingesting WRPU decreased. The possible reason is that WRPU does not supply sufficient nutrients for mealworm growth, and the impurities and odor present in WRPU affect the appetite of the mealworms. The microbial community analysis indicated that WRPU exerts a considerable effect on the gut microorganism of mealworms. These findings confirm that mealworms degrade WRPU.     

Data quality assessment for studies investigating microplastics and nanoplastics in food products: Are current data reliable?

● Data quality assessment criteria for MP/NPs in food products were developed. ● Data quality of 71 data records (69 of them only focused on MPs) was assessed. ● About 96% of the data records were considered unreliable in at least one criterion. ● Improvements need to be made regarding positive controls and polymer identification. ● A mismatch between MP/NPs used in toxicity studies and those in foods was recorded. Data on the occurrence of microplastics and nanoplastics (MP/NPs) in foods have been used to assess the human health risk caused by the consumption of MP/NPs. The reliability of the data, however, remains unclear because of the lack of international standards for the analysis of MP/NPs in foods. Therefore, the data quality needs to be assessed for accurate health risk assessment. This study developed 10 criteria applicable to the quality assessment of data on MP/NPs in foods. Accordingly, the reliability of 71 data records (69 of them only focused on MPs) was assessed by assigning a score of 2 (reliable without restrictions), 1 (reliable but with restrictions), or 0 (unreliable) on each criterion. The results showed that only three data records scored 2 or 1 on all criteria, and six data records scored 0 on as many as six criteria. A total of 58 data records did not include information on positive controls, and 12 data records did not conduct the polymer identification, which could result in the overestimation or underestimation of MP/NPs. Our results also indicated that the data quality of unprocessed foods was more reliable than that of processed foods. Furthermore, we proposed a quality assurance and quality control protocol to investigate MP/NPs in foods. Notably, the characteristics of MP/NPs used in toxicological studies and those existing in foods showed a remarkable discrepancy, causing the uncertainty of health risk assessment. Therefore, both the estimated exposure of MP/NPs and the claimed potential health risks should be treated with caution.     

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.     

Stress response to nanoplastics with different charges in Brassica napus L. during seed germination and seedling growth stages

● Higher concentrations of PS, PS-NH₂ and PS-SO₃H inhibited seed germination. ● PS, PS-NH₂ and PS-SO₃H influenced seedling growth in a dose-dependent manner. ● PS, PS-NH₂ and PS-SO₃H reduced essential nutrients uptake and plant quality. ● PS, PS-NH₂ and PS-SO₃H increased antioxidant enzyme activities and MDA content. ● Nanoplastic toxicity was related to surface charges. Nanoplastic pollution has become a significant problem in farmland systems worldwide. However, research on the effects of nanoplastics (NPs) with different charges on field crops is still limited. In our study, NPs with different charges, including unmodified polystyrene nanoplastics (PS), positively charged polystyrene nanoplastics (PS-NH₂), and negatively charged polystyrene nanoplastics (PS-SO₃H), were investigated for their impacts on seed germination and seedling growth of rape. The results showed that seed water uptake (after 12 h), seed germination, seed vigour, and relative root elongation were all significantly reduced under exposure to NPs (200 mg/L). Similarly, remarkable decreases in plant biomass (root weight, shoot weight), growth (root length, plant height), photosynthesis ability (chlorophyll a, chlorophyll b, carotenoids), essential nutrient uptake (Fe, Mn, Zn, Cu), and plant quality (soluble protein, soluble sugar, crude fibre content) of rape seedlings were also observed after exposure to NPs. Among the three kinds of NPs, PS-NH₂ showed stronger effects. Moreover, superoxide dismutase, peroxidase, and catalase activities of rape seedlings were changed, and the content of malondialdehyde was significantly increased under exposure to NPs. Furthermore, positively charged PS-NH₂ showed stronger effects on the phenotype, physiology, biochemistry, nutrient uptake, and plant quality of rape. Notably, a comprehensive toxicity evaluation revealed that PS-NH₂ had the strongest toxicity to rape. The present study provides important implications for the interaction and risk assessment of NPs and crops in soil-plant systems.     

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.     

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.     

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.     

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.     

Interaction and combined toxicity of microplastics and per- and polyfluoroalkyl substances in aquatic environment

● Adsorption of PFASs on MPs and its mechanisms are critically reviewed. ● MPs could alter the transport and transformation of PFASs in aquatic environments. ● Combined toxicity of MPs and PFASs at organismal and molecular levels is discussed. Microplastics (MPs) are recognized as vectors for the transport of organic contaminants in aquatic environments in addition to their own adverse effects on aquatic organisms. Per- and polyfluoroalkyl substances (PFASs) are widely present in aquatic environments due to their widespread applications, and thus coexist with MPs. Therefore, we focus on the interaction of MPs and PFASs and related combined toxicity in aquatic environments in this work. The adsorption of PFASs on MPs is critically reviewed, and new mechanisms such as halogen bonding, π-π interaction, cation-π interactions, and micelle formation are proposed. Moreover, the effect of MPs on the transport and transformation of PFASs in aquatic environments is discussed. Based on four typical aquatic organisms (shellfish, Daphnia, algae, and fish), the toxicity of MPs and/or PFASs at the organismal or molecular levels is also evaluated and summarized. Finally, challenges and research perspectives are proposed, and the roles of the shapes and aging process of MPs on PFAS biogeochemical processes and toxicity, especially on PFAS substitutes, are recommended for further investigation. This review provides a better understanding of the interactions and toxic effects of coexisting MPs and PFASs in aquatic environments.     

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.     

Photosensitivity sources of dissolved organic matter from wastewater treatment plants and their mediation effect on 17α-ethinylestradiol photodegradation

● EE2 photodegradation behavior in the presence of four WWTPs’ DOM was explored. ● The ³DOM* played a major role in the EE2 photodegradation mediated by WWTPs’ DOM. ● The A²/O process DOM contained more aromatic and oxygen-containing substances. ● Possible photosensitivity sources of DOM in the A²/O process were proposed. Dissolved organic matter (DOM) from each treatment process of wastewater treatment plants (WWTPs) contains abundant photosensitive substances, which could significantly affect the photodegradation of 17α-ethinylestradiol (EE2). Nevertheless, information about EE2 photodegradation behavior mediated by DOM from diverse WWTPs and the photosensitivity sources of such DOM are inadequate. This study explored the photodegradation behavior of EE2 mediated by four typical WWTPs’ DOM solutions and investigated the photosensitivity sources of DOM in the anaerobic-anoxic-oxic (A²/O) process. The parallel factor analysis identified three varying fluorescing components of these DOM, tryptophan-like substances or protein-like substances, microbial humus-like substances, and humic-like components. The photodegradation rate constants of EE2 were positively associated with the humification degree of DOM (P < 0.05). The triplet state substances were responsible for the degradation of EE2. DOM extracted from the A²/O process, especially in the secondary treatment process had the fastest EE2 photodegradation rate compared to that of the other three processes. Four types of components (water-soluble organic matter (WSOM), extracellular polymeric substance, humic acid, and fulvic acid) were separated from the A²/O process DOM. WSOM had the highest promotion effect on EE2 photodegradation. Fulvic acid-like components and humic acid-like organic compounds in WSOM were speculated to be important photosensitivity substances that can generate triplet state substances. This research explored the physicochemical properties and photosensitive sources of DOM in WWTPs, and explained the fate of estrogens photodegradation in natural waters.     

Electroconductive RGO-MXene membranes with wettability-regulated channels: improved water permeability and electro-enhanced rejection performance

● Electroconductive RGO-MXene membranes were fabricated. ● Wettable membrane channels were established between RGO and MXene nanosheets. ● Hydrophilic MXene reduces the resistance of water entering the membrane channels. ● Water permeance of RGO-MXene membrane is 16.8 times higher than that of RGO membrane. ● Electro-assistance can enhance the dye rejection performance of RGO-MXene membrane. Reduced graphene oxide (RGO) membranes are theoretically more conducive to the rapid transport of water molecules in their channels compared with graphene oxide (GO) membranes, as they have fewer oxygen-containing functional groups and more non-oxidized regions. However, the weak hydrophilicity of RGO membranes inhibits water entry into their channels, resulting in their low water permeability. In this work, we constructed wettable RGO-MXene channels by intercalating hydrophilic MXene nanosheets into the RGO membrane for improving the water permeance. The RGO-MXene composite membrane exhibits high pure water permeance of 62.1 L/(m²·h·bar), approximately 16.8 times that of the RGO membrane (3.7 L/(m²·h·bar)). Wettability test results and molecular dynamics simulations suggest that the improved water permeance results from the enhanced wettability of RGO-MXene membrane and increased rate of water molecules entering the RGO-MXene channels. Benefiting from good conductivity, the RGO-MXene membrane with electro-assistance exhibits significantly increased rejection rates for negatively charged dyes (from 56.0% at 0 V to 91.4% at 2.0 V for Orange G) without decreasing the permeate flux, which could be attributed to enhanced electrostatic repulsion under electro-assistance.     

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.     

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.     

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.