npj Clean Water最新文献

Ultrafiltration technology is one of the most efficient methods to address the issues of enhanced oil recovery-produced petroleum wastewater (EOR-PW) treatment. However, membrane fouling significantly impairs the efficiency of PW treatment. Moreover, the impacts of the complex components (e.g., salt ions, heavy metal ions, and pH level) in PW on membrane performance and the underlying mechanisms (i.e., fouling modes and interactive force) need further exploration. Herin, a novel ZrO₂/sericin polyacrylonitrile (ZrSS) ultrafiltration membrane was developed for PW treatment, and the impacts and mechanisms of contaminants in PW on membrane filtration performance were systematically investigated using synchrotron-based technology and extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) analysis. The synchrotron-based characterization results indicate the successful fabrication of the ZrSS membrane and the uniform distribution of ZrO₂/sericin nanocomposites (ZrSS NCs) within the membrane matrix. Optimization results show that the 3ZrSS membrane exhibits the highest water flux of 337.21 LMH and oil rejection of 99.80%. There are 67.58% and 11.04% improvements compared to the pristine PAN (polyacrylonitrile) membrane. Under alkaline pH, high salt ion (NaCl) strength, and low heavy metal ion (Ba²⁺) concentration, the 3ZrSS membrane experienced the least fouling (22.68% water flux decline). XDLVO theory elucidates that, under such conditions, there is a strong repulsive U^TOT (total interaction force) between oil droplets and the 3ZrSS membrane, which is demonstrated via the strong repulsive EL (electrostatic double layer) force. The 3ZrSS membrane maintained 84.84% of its initial water flux after a 72 h long-term filtration. After four cycled filtration, the 3ZrSS membrane kept an extremely high FRR (flux recovery rate) of 98.83%. This study is anticipated to offer technical, theoretical, and practical insights for the on-demand PW treatment.

To address the instability challenges of Partial Nitrification and Anammox (PNA) at low temperatures, this study introduces a temperature-based nitrogen removal process and demonstrates its feasibility in a pilot-scale system. The temperature-based strategy allows for the selective enhancement of anammox at higher temperatures (>20 °C) or denitrification at moderate and lower temperatures (≤20 °C). Nitrogen removal efficiencies of 93.8%, 72.1%, and 59.1% were achieved under >20 °C, 15–20 °C, and <15 °C, with corresponding effluent qualities of 3.0 mg/L, 9.6 mg/L, and 13.7 mg/L. As temperatures decreased, anammox contributions to nitrogen removal weakened from 88.4% to 8.2%, while denitrification contributions increased from 10.1% to 90.1%. Anammox bacteria exhibit a competitive advantage over denitrifying bacteria at higher temperatures, evidenced by the abundance of Candidatus Kuenenia at 7.13%. Denitratesoma was enriched to 3.47% at moderate and low temperatures, effectively supporting nitrogen removal robustness. This study provides insights into the seasonal optimization of mainstream anammox processes.

Detecting and quantifying biofouling is a challenging process inside a seawater reverse osmosis (SWRO) module due to its design complexity and operating obstacles. Herein, deep Convolutional Neural Network (CNN) models were developed to accurately calculate the cross-sectional biofilm thickness (vertical plane) through membrane surface images (horizontal plane). Models took membrane surface image as input; the classification model (CNN-Class) predicted fouling classification, while the regression model (CNN-Reg) predicted the average biofilm thickness on the membrane surface. CNN-Class model showed 90% accuracy, and CNN-Reg reached a moderate mean difference of ±24% in predicting the classification and biofilm thickness, respectively. Both models performed well and validated with 80% accuracy in classification and a mean difference of ±18% in biofilm thickness prediction from a new set of unseen live OCT images. The developed CNN models are a novel technology that has the potential to be implemented in desalination plants for early decision-making and biofouling mitigation.

Molybdenum disulfide (MoS₂) can be used as a potential photocatalyst for the removal of emerging contaminants (ECs) under visible light (Vis). However, the high carrier recombination rate and aggregation restrict pure MoS₂ application. The hydrothermal method was used to prepare a novel MoS₂/BaSO₄/zeolite (Z) composite (MBZ), which was used to activate peroxymonosulfate (PMS) under visible light for sulfadiazine (SDZ) degradation. The MBZ showed a moderate E_g value (2.59 eV), indicating good visible-light absorption. The physicochemical and photoelectrochemical properties were analyzed, revealing that the hybrid MBZ significantly enhanced photoinduced carrier generation, separation, and transfer. The MBZ exhibited 2.38-, 3.24-, and 1.36-fold higher SDZ removal reaction rates than Z, BaSO₄, and MoS₂ in the PMS/Vis system. The addition of EDTA-2Na notably decreased the degradation rate (79.58–89.88%), indicating the significant role of h⁺. This work provides a new approach to the design of semiconductor/insulator photocatalysts and constructs a promising catalytic oxidation system for the green remediation of EC wastewater.

Enhancing the sustainability of catalysts is crucial for the practical application of piezo-photocatalytic degradation of sewage. This study introduces a novel approach by fabricating highly stretchable piezoelectric composite nanofiber films through electrospinning TPU/g-C₃N₄ mixture. The tight integration of TPU nanofibers with g-C₃N₄ few-layers pre-stresses g-C₃N₄ and strengthens the mechanical properties of the composite films, achieving a maximum tensile strain and stress of 862% and 6.90 MPa, respectively. With the assistance of 300 W ultrasound, the photocatalytic capability of the TPU/0.2g g-C₃N₄ composite nanofiber film is enhanced by 43% and maintains nearly 100% of its initial performance after 12 repeated experiments. The electronic, piezoelectric, and optical properties of uniaxial-strained monolayer g-C₃N₄ are studied by first-principles calculations, revealing that stretching in the armchair direction can double the in-plane piezoelectric coefficient, while compression in the armchair direction simultaneously alters the charge distribution within the heptazine rings and modulates the adsorption sites and energy for oxygen molecule. Therefore, ultrasound-induced dynamic strains can significantly enhance the photocatalytic effect. The degradation of electronic industrial wastewater demonstrates the practical application potential of the catalytic composite nanofiber film. This research offers a pioneering strategy for the development of efficient photocatalytic systems for sewage treatment.

In order to solve the high energy consumption and other problems of the post-pump filter, an efficient pre-pump filter, pontoon mesh rotary filter, has been developed. In this study, the physical full test under the factors of flow rate, sand content, flushing flow rate, and filtration time was carried out using filtration efficiency as an index. The results were analyzed using quantile analysis, PPR, MLP, and Sobol index, and a prediction model was established, in which the MLP-based prediction model was more effective. The influence ranking of single and double factors were determined and the optimum working conditions were proposed. The results of the study provide a reference for filters, enrich the theory of micro-pressure filtration, and provide operational parameters for filter applications.

Anaerobic digestion (AD) is a crucial bioenergy source widely applied in wastewater treatment. However, its efficiency improvement is hindered by complex microbial communities and sensitivity to feedstock properties. We, thus, propose a hybrid quantum-classical machine learning (Q-CML) regression algorithm using a quantum circuit learning (QCL) strategy. Combining a variational quantum circuit with a classical optimiser, this approach predicts biogas production from operational data of 18 full-scale mesophilic AD sites in the UK. Tailored for noisy intermediate-scale quantum (NISQ) devices, the low-depth QCL model outperforms conventional regression methods (R²: 0.53) and matches the performance of a classical multi-layer perceptron (MLP) regressor (R²: 0.959) with significantly fewer parameters and better scalability. Comparative analysis highlights the advantages of quantum superposition and entanglement in capturing intricate correlations in AD data. This study positions Q-CML as a cutting-edge solution for optimising AD processes, boosting energy recovery, and driving the circular economy.

Anionic dyes contaminate water and severely disrupt aquatic ecosystems, urgently demanding effective treatment solutions for safety. This study explores the synthesis of unsaturated MIL-101(Cr) and its exceptional performance in removing anionic dyes from polluted water systems. The synthesized MIL-101(Cr) exhibits medium Lewis’s acid and strong Brønsted acid sites, a high specific surface area (>3000 m²/g), and a Zeta potential of 30 mV, contributing to its strong adsorption capability. Adsorption studies reveal Langmuir isotherm model fitting, with maximum adsorption capacities of 4231, 1266, and 568 mg/g for Acid Blue 92, Congo Red, and Acid Blue 90, respectively. The chemisorption process follows pseudo-second-order kinetics and is spontaneous and exothermic. MIL-101(Cr) demonstrates chemical and water stability, maintaining over 80% removal efficiency after five recycling cycles. This research provides valuable insights into treating anionic dye-contaminated wastewater using MIL-101(Cr) as an efficient adsorbent.

Disposal of antibiotics and antimicrobial-resistant enteric bacteria (ARB) into water from various sources is responsible for maintaining ARB in the environment. Relative prevalence and circulation of ARB may vary across water sources. We hypothesized that these ARBs with different resistance genes are distributed in various freshwater sources and are related to each other. We screened 155 enteric bacterial isolates from eight different water sources in Dhaka. The prevalence of ARB and MDR enteric bacteria in water was significantly associated (p value < 0.05) with the sources. The genotypic analysis of bla_TEM, qnrB, tetA, mcr-1, and sul-1 revealed higher similarity of the isolates from freshwater with previously reported isolates from clinical samples. Water sources with direct exposure to antibiotics had a significantly higher frequency of genotypic and phenotypic resistance. This study calls for continuous monitoring of water sources and strengthening the treatment of antibiotic and ARB-containing effluents in Bangladesh.

Load reduction is essential for mitigating the transmission risk of antibiotic resistance genes (ARGs) from livestock wastewater. This study examined the potential and mechanisms of Myriophyllum elatinoide-planted system in reducing ARGs in swine wastewater. Field experiment showed a progressive decline in ARG diversity and abundance as pond number increased, which was attributed to bacterial community shift and mobile genetic element-mediated horizontal transfer. This was corroborated by hydroponic experiment, where removal rates of antibiotics, antibiotic-resistant bacteria, and ARGs reached 64.82–87.83%, 66.27–98.39%, and 93.63–99.82%. Mechanistically, such a reduction could be achieved through direct uptake by plant roots and shoots, and indirectly by alleviating the selection pressure from antibiotic residues. Furthermore, M. elatinoides treatment substantially decreased ARG burdens in wastewater-receiving water (71.40–96.68%) and soils (36.81–85.69%). Our findings present a feasible and sustainable strategy for mitigating swine wastewater-borne ARGs, aiding in the fight against the spread of antibiotic resistance.