Water Research最新文献

Emerging contaminants in water represent long-term and unpredictable threats to both environmental and human health due to their persistence and bioaccumulation. Current research predominantly focuses on their removal rather than sustained monitoring. This review comprehensively investigates advanced sensor technologies for detecting these contaminants in water, critically evaluating biosensors, optical sensors, electrochemical sensors, and nanomaterial sensors. Elucidating the operational principles, performance metrics such as detection thresholds, and the pros and cons of their practical applications, the review addresses a significant research gap in environmental monitoring. Moreover, it enhances understanding of sensor effectiveness, which in turn guides researchers in selecting the right sensor types for various environmental scenarios. Furthermore, by emphasizing the integration of nanotechnology and the standardization of evaluation protocols, it promotes the development of robust, deployable sensing solutions. Ultimately, this leads to the proposal of a strategic framework aimed at significantly improving the detection capabilities of emerging contaminants and supporting the preservation of environmental health.

The Pollution source identification (PSI) is an important issue on river water quality management especially for urban receiving water. Numerical inversion method is theoretically an effective PSI technique, which employs monitored downstream pollutant breakthrough curves to identify the pollution source. In practice, it is important to know how much monitoring data should be accumulated to provide PSI results with acceptable accuracy and uncertainty. However, no literature reports on this key point and it seriously handers the numerical PSI technology to mature practical applications. To seek a monitoring guideline for PSI, we conducted extensively numerical experiments for single-point source instantaneous release taking Bayesian-MCMC method as the baseline inversion technique. The crucial time (T_c) phenomenon was found during the data accumulation process for Bayesian source inversion. After T_c, estimated source parameters subsequent sustained low error levels and uncertainty convergence. Results shown the presence of T_c impacted by the number and location of monitoring sections, while monitoring frequency and data error do not. Under different river hydrodynamic conditions, relative crucial time (Λ) is determined by the river's Peclet number, and minimum effective Λ was controlled by dispersion coefficient (D_x). Analytic spatial structure of Λ(U, D_x) was uncovered and this relationship successfully explained by the information entropy theory. Based on these findings, a novel design method of PSI emergency monitoring network for preparedness plan and a practical framework of PSI for emergency response were established. These findings fill the important knowledge gap in PSI applications and the guidelines provide valuable references for river water quality management.

Ethanol feeding has been widely documented as an economical and effective strategy for establishing direct interspecies electron transfer (DIET) during anaerobic digestion. However, the mechanisms involved are still unclear, especially on correlation between intracellular electron transfer in electroactive bacteria and their gene expression for electrically conductive pili (e-pili), the most essential electrical connection component for DIET. Upon cooling from room temperature, the conductivity of digester aggregates with ethanol exponentially increased by an order of magnitude (from 45.5 to 125.4 μS/cm), whereas which with its metabolites (acetaldehyde [from 40.5 to 54.4 μS/cm] or acetate [from 32.1 to 50.4 μS/cm]) did not increase significantly. In addition, the digester aggregates only with ethanol were observed with a strong dependence of conductivity on pH. Metagenomic and metatranscriptomic analysis showed that Desulfovibrio desulfuricans was the most dominant and metabolically active bacterium that contained and highly expressed the genes for e-pili. Abundance of genes encoding the total type IV pilus assembly proteins (6.72E-04 vs 1.24E-03, P < 0.05), PilA that determined the conductive properties (2.22E-04 vs 2.44E-04, P > 0.05), and PilB that proceeded the polymerization of pilin (1.56E-04 vs 3.52E-03, P < 0.05) with ethanol was lower than that with acetaldehyde. However, transcript abundance of these genes with ethanol was generally higher than that with acetaldehyde. In comparison to acetaldehyde, ethanol increased the transcript abundance of genes encoding the key enzymes involved in NADH/NAD⁺ transformation on complex I and ATP synthesis on complex V in intracellular electron transport chain. The improvement of intracellular electron transfer in D. desulfuricans suggested that electrons were intracellularly energized with high energy to activate e-pili during DIET.

Cyanobacteria-derived organic carbon has been reported to intensify greenhouse gas emissions from lacustrine sediments. However, the specific processes of CH₄ and CO₂ production and release from sediments into the atmosphere remain unclear, especially in eutrophic lakes. To investigate the influence of severe cyanobacteria accumulation on the production and migration of sedimentary CH₄ and CO₂, this study examined the different trophic level lakes along the middle and lower reaches of the Yangtze River. The results demonstrated that eutrophication amplified CH₄ and CO₂ emissions, notably in Lake Taihu, where fluxes peaked at 929.9 and 7222.5 μmol/m²·h, mirroring dissolved gas levels in overlying waters. Increased sedimentary organic carbon raised dissolved CH₄ and CO₂ concentrations in pore-water, with isotopic tracking showing cyanobacteria-derived carbon specifically elevated CH₄ and CO₂ in surface sediment pore-water more than in deeper layers. Cyanobacteria-derived carbon deposition on surface sediment boosted organic carbon and moisture levels, fostering an anaerobic microenvironment conducive to enhanced biogenic CH₄ and CO₂ production in surface sediments. In the microcosm systems with the most severe cyanobacteria accumulation, average CH₄ and CO₂ concentrations in surface sediments reached 6.9 and 2.3 mol/L, respectively, surpassing the 4.7 and 1.4 mol/L observed in bottom sediments, indicating upward migration of CH₄ and CO₂ hotspots from deeper to surface layers. These findings enhance our understanding of the mechanisms underlying lake sediment carbon emissions induced by eutrophication and provide a more accurate assessment of lake carbon emissions.

Volatile fatty acids (VFAs) serve as building blocks for a wide range of chemicals, but it is difficult to extract VFAs from pH-neutral wastewater using evaporation methods because of the ionized form. This study presents a new membrane electrolysis distillation (MED) process that extracts VFAs from such fermentation solutions. MED uniquely integrates pH regulation and joule heating to facilitate the efficient evaporation of VFAs. This integration occurs alongside a hydrophobic membrane that ensures effective gas-liquid phase separation. Operating solely on electricity, MED achieved an acid flux rate of 12.03 g/m²/h at 6V. In contrast, the control results without the joule heating or pH swing only obtained a 0.23 g/m²/h and 0.32 g/m²/h flux, respectively. In addition, a physicochemical model was developed to assess the impacts of temperature on membrane surface pH. This system enhances resource recovery from waste streams and helps achieve a circular carbon economy.

Aquifers, which provide drinking water for nearly half the world's population, face significant challenges from microbial contamination, particularly from waterborne viruses such as human adenovirus (HAdV), norovirus (NoV) and enterovirus (EV). This study, conducted as part of the UPWATER project, investigates the sources of urban groundwater contamination using viral passive sampling (VPS) and target enrichment sequencing (TES). We assessed the abundance of eight viral pathogens (HAdV, EV, NoV genogroup I and II, rotavirus, influenza A virus, hepatitis E virus and SARS-CoV-2) and investigated the virome diversity of groundwater in the aquifer of the Besòs River Delta in Catalonia. Over a period of 7 months, we collected 114 samples from the aquifer using nylon and nitrocellulose membranes to adsorb viruses over a 10-day period. Human faecal contamination was detected in nearly 50 % of the groundwater samples, with mean HAdV total counts ranging from 1.23E+02 to 3.66E+03 GC, and occasional detections of EV and NoV GI and GII. In addition, deep sequencing revealed a diverse virome in the aquifer, with detection of human pathogens, including adenovirus, astrovirus, calicivirus, enterovirus, herpesvirus, papillomavirus and rotavirus. Time-integrated sampling using VPS increases the likelihood of virus detection and, when combined with TES, can provide a deeper understanding of virus prevalence in this important water compartment. This approach is expected to streamline long-term monitoring efforts and enable small communities or water managers with limited resources to effectively manage their groundwater reservoirs.

Submerged macrophytes remediation is a commonly used technique for improving water quality and restoring habitat in aquatic ecosystems. However, the drivers of success in the submerged macrophytes assembly process and their specific impacts on methane emissions are poorly understood. Thus, we conducted a mesocosm experiment to test the growth plasticity and carbon fixation of widespread submerged macrophytes (Vallisneria natans) under different nutrient conditions. A refined dynamic chamber method was utilized to concurrently collect and quantify methane emission fluxes arising from ebullition and diffusion processes. Significant correlations were found between methane flux and variations in the physiological activities of V. nantas by the fluorescence imaging system. Our results show that exceeding tolerance thresholds of ammonia in the water significantly interfered with the photosynthetic systems in submerged leaves and the radial oxygen loss in adventitious roots. The recovery process of V. natans accelerated the consumption of dissolved oxygen, leading to increase in the populations of methanogen (153.3 % increase of mcrA genes) and subsequently elevating CH₄ emission fluxes (23.7 %) under high nutrient concentrations. Conversely, V. natans increased the available organic carbon under low nutrient conditions by radial oxygen loss, further increasing CH₄ emission fluxes (94.7 %). Quantitative genetic and modeling analyses revealed that plant restoration processes drive ecological niche differentiation of methanogenic and methane oxidation microorganisms, affecting methane release fluxes within the restored area. The speciation process of V. natans is incapable of simultaneously meeting improved water purification and reduced methane emissions goals.

The main pressing problems should be solved for heterogeneous catalysts in activation of peroxymonosulfate (PMS) are sluggish mass transfer kinetics and low intrinsic activity. Here, oxygen vacancies (Vo)-rich of Co₃O₄ nanosheets were anchored on the superficies of spirulina-based reduced graphene oxide-konjac glucomannan (KGM) aerogel (R-Co₃O_4-x/SRGA). The porous structure and superhydrophilicity conferred by KGM maximized the diffusion and transport of reactant. More interestingly, R-Co₃O_4-x/SRGA came true self-suspension rather than conventional self-floating without the aid of external force, maximizing space utilization and facilitating catalysts recovery. Anchored R-Co₃O_4-x nanosheets acted as “engines” to drive the reaction. Density functional theory (DFT) manifested Vo was capable of breaking the symmetry of the electronic structure of Co₃O₄. The formation of asymmetric active sites (Vo) was revealed to modulate the d-band center, enhanced affinity for PMS, and promoted evolution of high-valent cobalt-oxo (Co(IV)=O) species. R-Co₃O_4-x/SRGA achieved complete removal of sulfamethoxazole (SMX) within 12 min. Furthermore, R-Co₃O_4-x/SRGA demonstrated exceptional stability in the presence of various environmental interference factors and continuous flow device. This insightful work cleverly integrates the macroscopic design of structure, and the microscopic regulation of active sites is expected to open up new opportunities for the development of water treatment.

The mainstream partial nitritation/anammox (PN/A) process represents a significant innovation in decarbonizing municipal wastewater treatment. However, its implementation is considerably hampered by the challenge of stable nitrite supply. In this study, a pilot-scale PN/A system receiving real sewage (20 m³) was operated at room temperature for nearly one year. Remarkable PN performance with relatively high nitrite accumulation ratio of 75.04 ± 10.05 % was obtained via in-situ free ammonia (FA) strategy. The ammonium concentration enriched in the zeolite increased significantly by 548.8 times compared to that in the aqueous phase by ion exchange. This substantial increase robustly inhibited nitrite-oxidizing bacteria (NOB), resulting in high relative abundance ratio of ammonia-oxidizing bacteria (AOB) to NOB of 37.93 ± 12.61 in the zeolite biofilm, compared to 10.22 ± 1.67 in suspended floc sludge. The significant differences in FA concentrations between zeolite biofilm and suspended floc sludge resulted in distinct spatial distribution disparities of AOB and NOB, which were central to achieving stable nitrite accumulation without complex multiple selective pressures. Consequently, compliant effluent with total nitrogen of 10.91 ± 4.23 mg N/L was achieved at 10.4-31.1 °C without external carbon source addition. The biocarriers in the anammox process played a key role in enhancing functional genes and electron flow, supporting anammox-dominated nitrogen removal. This study presents a flexible and adaptable strategy for mainstream nitrite shunting, highlighting its potential for large-scale implementation of mainstream anammox treatment.

Clostridium perfringens (CP) is a common cause of foodborne infection, leading to significant human health risks and a high economic burden. Thus, effective CP disease surveillance is essential for preventive and therapeutic interventions; however, conventional practices often entail complex, resource-intensive, and costly procedures. This study introduced a data-driven machine learning (ML) modeling framework for CP-related disease surveillance. It leveraged an integrated dataset of municipal wastewater microbiome (e.g., CP abundance), crowdsourced (CP-related web search keywords), and environmental data. Various optimization strategies, including data integration, data normalization, model selection, and hyperparameter tuning, were implemented to improve the ML modeling performance, leading to enhanced predictions of CP cases over time. Explainable artificial intelligence methods identified CP abundance as the most reliable predictor of CP disease cases. Multi-omics subsequently revealed the presence of CP and its genotypes/toxinotypes in wastewater, validating the utility of microbiome-data-enabled ML surveillance for foodborne diseases. This ML-based framework thus exhibits significant potential for complementing and reinforcing existing disease surveillance systems.