The ubiquitous occurrence of microplastics (MPs) in drinking water systems has raised escalating concerns for microbial health and water security. Although the occurrence and toxicological risks of MPs have been increasingly documented, their roles in compromising disinfection efficacy remain insufficiently understood. Here, we systematically elucidate how MPs enhance bacterial resistance to two widely used disinfectants, chlorine and chloramine, in drinking water systems. MPs increased bacterial survival by 1.18-2.58 fold, with protection intensifying at higher MP and disinfectant concentrations (0-2.0 mg/L). This phenomenon was closely associated with disinfectant-induced oxidative stress, which promoted rapid bacterial attachment on MP surfaces, increasing attachment rates from 15.88% to over 80% after 0.5 h exposure to 2.0 mg/L chlorine. Fourier-transform infrared spectroscopy and extended Derjaguin-Landau-Verwey-Overbeek modeling revealed that oxidative modification of both MP surfaces and bacterial envelopes enhanced interfacial compatibility and strengthened MP-bacteria interaction energies, reducing the adhesion energy barrier from 140.69 kT to 45.83 kT and facilitating irreversible colonization. Additionally, MPs accelerated disinfectant decay and released dissolved organic matter, generating nutrient-enriched microhabitats that supported prolonged bacterial persistence. High-throughput sequencing further showed that MP-associated biofilms selectively enriched adhesive and disinfectant-resistant taxa, reshaping biofilm communities under disinfection stress. Collectively, these findings demonstrate that MPs compromise disinfection efficacy through synergistic mechanisms involving physical shielding, chemical scavenging, and microhabitat restructuring, highlighting the imperative to integrate MP-associated risks into microbial safety management and regulatory frameworks for drinking water systems.

Chlorination is widely applied in municipal wastewater treatment for pathogen inactivation; however, it may inadvertently induce bacterial stress responses and promote the spread of antibiotic resistance genes (ARGs), posing potential environmental risks. The mechanisms underlying chlorination-enhanced horizontal ARG transfer in reclaimed water remain unclear. To address this knowledge gap, we investigated resistance evolution and horizontal transfer in reclaimed water following chlorination. Chlorination (0.5-5.0 mg/L) increased the absolute abundance of antibiotic-resistant bacteria by 1.38-4.93 log units during regrowth. At 3.0 mg/L chlorine with a 3-day regrowth, the bacterial community was profoundly reshaped, with dominant phyla shifting from Proteobacteria, Patescibacteria, and Bacteroidota in the control to a predominance of Proteobacteria (96.31%). Sul1 expression was upregulated 9.95-fold and ARG conjugative transfer increased by 13.2-fold. These changes were accompanied by significant upregulation of genes associated with resistance spread and stress responses, including efflux pump genes (acrD, ermA, tolC), outer membrane protein gene (ompA), and dormancy regulator gene (rpoS). Collectively, these findings demonstrate that sub-lethal chlorination facilitates ARG dissemination in reclaimed water by inducing bacterial stress responses and conjugation, highlighting the need for optimized disinfection strategies to reduce the environmental spread of antibiotic resistance.

In biological wastewater treatment units, bacteria can self-assemble into flocs with heterogeneous structural characteristics. These flocs, varying in density, create dynamic microenvironments that reshape bacterial community assembly and influence the dissemination of antibiotic resistance, a process that is not yet fully understood. This study investigated the evolution of antibiotic resistance across floc density gradients to elucidate the key driving mechanisms. An increase in floc density from 1.0020 g mL(-1) to 1.0029 g mL(-1) triggered a fourfold rise in the absolute abundance of antibiotic-resistant bacteria (ARB) (p < 0.05), with their relative abundance increasing from 64% to 89%. Microbial community analysis revealed significant shifts at both the phylum and genus levels across varying floc densities (p < 0.05), likely driven by floc density-mediated changes in nutrient availability. Notably, the resource-sensitive Methylophilaceae declined in denser flocs, whereas the nutrient-tolerant Saccharimonadales and Blastocatellaceae proliferated. Furthermore, both the absolute and relative abundances of key antibiotic resistance genes (ARGs), including class 1 integron (intI1), sulfamethoxazole- (sul1 and sul2) and ciprofloxacin-related resistance genes (qnrB and qnrS), increased with increasing sludge density. Particularly, sul1 and sul2 exhibited 1.9-fold and 4.5-fold upregulations, respectively (p < 0.05). These findings highlight strong linkages among floc density, bacterial community composition and antibiotic resistance profiles, suggesting that floc density modulates resistance by reshaping the bacterial community composition in activated sludge. This study provides insights into the ecological mechanisms governing antibiotic resistance in wastewater treatment systems, aiding improved risk assessment and management strategies.

Microgrids are essential for achieving stable, carbon-neutral power systems, with park-level projects being key implementations. However, research gaps persist in addressing complex operational scheduling and multistakeholder coordination challenges. This study develops a novel park-level microgrid integrating biomass-togas, carbon removals, and hydrogen storage to achieve net-zero emissions. We establish a bi-level optimization framework that integrates long-term planning and short-term operations, where the upper level minimizes lifecycle costs while the lower level simultaneously optimizes operational profits and risk mitigation. The nonlinear problem is solved using a decomposition-based multi-objective evolutionary algorithm. A hybrid mechanism combining Shapley value principles with Nash bargaining theory is further proposed to equitably allocate benefits based on stakeholders' contributions to profit, risk reduction, and carbon mitigation. Empirical analysis shows carbon removal technologies can enhance system stability and energy utilization. Medium-to-high carbon prices boost operating profits by 131.7%-170.1 % and lower capital costs by 21.8%-29.9 %, while achieving negative emissions. The proposed model improves stakeholder satisfaction by 7.8 % compared to traditional methods. Sensitivity analysis reveals hydrogen prices below 19 & YEN;/kg risk losses, recommending high carbon price deployment for financial risk mitigation. This framework provides a robust approach for designing sustainable, economically viable park-level microgrids, enabling equal multi-stakeholder benefit allocation and risk-aware operational optimization.

Electrodialysis (ED) uses electric energy to conduct the desalination, while bipolar membrane reverse electrodialysis (BMRED) converts the chemical energy containing in acids and alkalis into electric energy. Here, a novel membrane stack (BMRED-ED) based on BMRED and ED was designed to realize the simultaneous energy selfsufficient desalination and energy output process. The stack was studied in two different operation modes systematically. Results of the open-loop operation mode demonstrate that the maximum power density ( P d , max ) can obtain a highest value of 4.53 W center dot m-2, center dot m- 2 , and the maximal average apparent permeability (alpha) alpha ) between the open circuit voltage (OCV) and OCV ) and theoretical electromotive force (EMF) EMF ) is 92.23 %. Results of the closed-loop operation mode indicate that the final desalination ratio ( xi del ) can attain as high as 89.57 %, and the corresponding energy utilization ratios of the desalination ( eta des ) and the energy output ( eta out ) are 0.90 % and 14.00 %, respectively. Moreover, the effect of desalinated salt solution concentrations and discharging current densities on the closed- loop operation performance are much more remarkable than that of cation species in the alkali and salt solutions. This work provides a feasible and competitive strategy for simultaneous energy self-sufficient desalination and energy output.

Drought stress has a significant impact on cotton growth, development, and productivity. This study conducted drought stress treatment and normal water treatment (control group) on 502 cotton accessions and analyzed data on eight phenotypic traits closely related to drought stress tolerance. The results showed that all indicators changed significantly under drought stress conditions compared to the control group, with varying degrees of response among different indicators. To comprehensively evaluate the drought resistance of cotton during the germination period, the values of drought resistance comprehensive evaluation (D-value), weight drought resistance coefficient (WDC-value), and comprehensive drought resistance coefficient (CDC-value) were calculated based on membership function analysis and principal component analysis. Cluster analysis based on the D-value divided the germplasm into five drought-resistant grades, followed by the selection of one extreme material, each from the strongly drought-resistant and strongly drought-sensitive groups. An evaluation model was established using stepwise regression analysis, including the following effective indicators: Relative Fresh Weight (RFW), Relative Hypocotyl Length (RHL), Relative Seeds Water Absorption Rate (RAR), Relative Germination Rate (RGR), Relative Germination Potential (RGP), and Relative Drought Tolerance Index (RDT). The validation of the D-value prediction model based on the Best Linear Unbiased Prediction (BLUP) showed that the results obtained from two independent biological replicates were highly consistent. The comprehensive evaluation system and screening indicators established in this study provide a reliable method for identifying drought tolerance during the germination period.

The installation of secondary water supply systems (SWSS) is essential for balancing water demands and ensuring reliable water supply in urban distribution networks. However, optimizing the operation of storage tanks to enhance overall system performance is a challenging task due to the interplay of multiple interconnected factors. This study presents a novel approach through a multi-objective simulation-based framework to determine optimal inflow profiles of storage tanks. It focuses on three key performance metrics: pressure fluctuations, pumping energy consumption, and water quality degradation. Through simulation analysis, this study successfully identified non-dominated trade-off alternatives, which were further validated using experimental investigations conducted in a laboratory-scale water supply system equipped with multiple SWSSs. Compared to traditional control strategies, the optimal compromise solution identified from the Pareto front demonstrated significant improvements: reducing pressure fluctuations by 82 %, cutting hydraulic retention time by 52 %, and lowering pumping energy consumption by 6 %, respectively. In dynamic real-world scenarios, where water demand and system conditions fluctuate constantly, the proposed approach can adaptively optimize system performance by leveraging a hot-start method based on prior solutions. This study provides a promising framework for optimizing the operation of urban storage tanks, striking a balance between pressure stability, water quality preservation, and energy efficiency. It thus serves as a valuable reference for managing complex urban water supply systems.

Cyanobacteria are competent hosts for antibiotic resistance genes, influencing the spread of bacterial resistance through their complex interactions within aquatic environments. However, the coevolution of antibiotic resistance between cyanobacteria and bacteria under sub-inhibitory antibiotic stresses remains unclear. To bridge this knowledge gap, we investigated the effects of Microcystis aeruginosa on modulating bacterial resistance evolution in aquatic ecosystems exposed to sub-inhibitory antibiotics. Results show that cyanobacteria reduced the abundance of antibiotic resistance bacteria (ARB) by 62 % to 93 % in antibiotic-free conditions and by up to 80 % under sub-inhibitory antibiotic concentrations. The concurrence of cyanobacteria and antibiotics significantly alter microbial community compositions, with Proteobacteria emerging as the dominant population (51 %-66 %) and Bacteroidota proliferating by 8.7-fold, alongside a significant enrichment of metabolism-related and pathogenic genes ( p < 0.05). Redundancy analysis revealed that ARB prevalence was positively correlated with the abundances of Proteobacteria and Bacteroidota, but negatively correlated with Cyanobacteria. Our findings suggest that cyanobacteria may reduce the spread of bacterial resistance both in antibiotic-free and sub-inhibitory antibiotic environments, by reshaping population interactions. These insights are crucial for evaluating the risk of antibiotic-driven bacterial resistance spread in cyanobacteria-rich environments and are vital for the protection and assessment of aquatic environmental quality.

Pressure estimation is crucial for efficient operation and management of water distribution networks (WDNs). However, it is often challenged by limited sensor observations. While graph neural networks (GNNs) have been used to improve hydraulic and water quality predictions of WDNs, their reliance on homogeneous graphs oversimplifies the diverse roles and interactions of hydraulic components, resulting in lower performance under dynamic system states. This research introduces a novel heterogeneous graph neural network (HGNN) framework, which models control units such as pumps and valves as distinct nodes while preserving their interactions through additional edge types. Experimental results using C-Town as a benchmark demonstrate that HGNN outperforms GNN in terms of accuracy, robustness, and adaptability, achieving a mean absolute percentage error (MAPE) of 1.88 % and a mean absolute error (MAE) of 1.70 m under a 95 % masking rate. Additionally, this study shows that optimal sensor placement reduces MAE by up to 15 %, and the proposed HGNN framework achieves high computational efficiency, highlighting its effectiveness in WDN analysis and management. This research offers an advanced and transferable approach for WDN pressure estimation, serving as a superior alternative to traditional pressure evaluation models.

The persistent use of antibiotics has exacerbated the spread of antibiotic-resistant bacteria (ARB) and antibiotic-resistant genes (ARGs) in aquatic environments, including drinking water systems. Pipeline biofilms, comprising over 95 % of microbial biomass, function as high-risk reservoirs for ARG accumulation and horizontal gene transfer (HGT). However, the roles of disinfection-induced biofilm aggregation in plasmid-mediated conjugation remains mechanistically obscure. This study investigated how sodium hypochlorite (NaClO), chlorine dioxide (ClO2), and their combination affect ARB selection and ARG conjugation in multispecies drinking water biofilms at environmentally relevant chlorine concentrations (0-2.0 mg/L). Results showed that exposure to either NaClO or ClO2 at 1.0 mg/L increased the relative abundance of ARB, while combined disinfection at 2.0 mg/L exerted selective pressure that further enhanced ARB enrichment. Sublethal chlorine levels increased conjugation frequencies within biofilms by 2.1- to 5.9-fold relative to untreated controls. Conjugation efficiency was positively correlated with bacterial surface colonization and metabolic activity (r = 0.95, p < 0.05). Mechanistic investigations revealed that chlorine exposure upregulated integrase genes, enriched potential ARG-hosting taxa, and preserved fimbrial structures, collectively facilitating donor-recipient interactions and promoting HGT. These findings elucidate the mechanistic pathways underlying disinfection-mediated horizontal gene transfer and provide critical insights into managing antibiotic resistance risks in drinking water systems.

Electroactive bacteria play a crucial role in electrocatalytic oxidation and reduction reactions within bioelectrochemical systems (BES). However, the influence of BES startup modes on the adhesion of electroactive bacteria and the underlying mechanisms remains elusive. We hypothesize that startup mode-induced microniches trigger changes in bacterial motility, which mediate bacterial adhesion on anodic surface. To test this hypothesis, we employed Shewanella oneidensis MR-1 as a model strain and launched investigations in singlechambered BES under both external voltage-free (EVF) and external voltage-applied (EVA) modes. Our results showed that the EVA mode facilitated MR-1 adhesion up to fourfold compared to the EVF mode. Surface chemistry analysis revealed that EVA mode, with proper external voltages (400-600 mV), enhanced substrate adsorption onto anodic surfaces by up to 410 %, significantly promoting bacterial cell movement and chemotactic migration towards anodic surfaces, thereby facilitating bacterial adhesion. Principal component analysis and structural equation modeling indicated that lactate adsorption capacity was the determining factor for bacterial adhesion under EVF mode, whereas external voltage diminished the effect of lactate on triggering cell motility and subsequent bacterial adhesion in the EVA mode. Our findings provide valuable insights into the initiation and enhancement of electrochemically active biofilm on electrode surfaces in BES.

Water consumption dynamics lead to pressure fluctuations at network nodes, potentially associated with pipe leakages or unreliable supply within a water distribution system. Efficient management of secondary water supply system (SWSS) could enhance inflow modes of its essential component (i.e., storage tank) of potential implication on pressure control and water quality maintenance. In this study, a novel computational framework was developed to determine the optimal inflow profiles of storage tanks, where a water supply system simulation model was integrated with the particle swarm algorithm-based optimization for demand peak staggering. Experimental investigations on an example water supply system revealed that, as compared to the control of float ball valves, the optimizing regulation of SWSS tanks remarkably reduced water pressure oscillations by approximately 70

Cyanobacterial blooms are expanding world-wide in freshwater and marine environments, and can cause serious ecological and environmental issues, which also contribute to the spread of antibiotic resistance genes (ARGs). However, the mechanistic understanding of cyanobacteria-mediated resistance dynamics is not fully elucidated yet. We selected Microcystis aeruginosa as a model cyanobacteria to illustrate how cyanobacteria mediate the evolution and transfer processes of bacterial antibiotic resistance. The results show that the presence of cyanobacteria significantly decreased the abundance of antibiotic resistant bacteria (ARB) and antibiotic resistant genes (ARGs) by 3%-99% and 2%-18%, respectively. In addition, it clearly altered bacterial community structure, with the dominant genera evolving from Acinetobacter (27%) and Enterobacter (42%) to Porphyrobacter (59%). The abundance of ARGs positively correlated with Proteobacteria and Firmicutes, rather than Cyanobacteria, and Bacteroidetes. In the presence of cyanobacteria, the transfer events of bacterial resistance genes via conjugation were found to decrease by 10%-89% (p < 0.05). Surprisingly, we found an extradentary high transfer frequency (about 0.1) for the ARGs via plasmid conjugation from the bacteria into M. aeruginosa population. It confirmed the role of cyanobacterial population as the competent hosts to facilitate ARGs spreading. Our findings provide valuable information on the risk evaluation of ARGs caused by cyanobacterial blooms in aquatic environments, key for the protection and assessment of aquatic environmental quality.

Bacterial colonization onto interior pipe walls is ubiquitous in drinking water systems, with the inevitable consequences on water quality safety. However, the mechanisms of how physicochemical properties of pipe materials interfering with cell-surface interactions and subsequent biofilm colonization in drinking water systems have not been fully unveiled. In this study, we investigated initial biofilm colonization onto polyvinyl chloride (PVC), polyethylene (PE) and stainless steel (STS) coupons having various surface roughness during one week incubation in bench reactors. Results display that increased surface roughness encouraged biofilm formation particularly on plastic materials. With the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) modeling analysis, the increment in surface roughness enlarged superficial area and hydrophobicity that reinforced van der Waals force and acid-base bacteria-surface interactions, thereof facilitating biofilm initialization and consequent accumulation. Meanwhile, the PVC and PE coupons attracted around six-fold and four-fold adhesive cells in contrast to the STS ones with the roughness of similar to 1.50 mu m, respectively. Unlike the STS that induced hydrophilic (repulsive) interactions, plastic materials encouraged hydrophobic (attractive) acid-base interactions and bacterial surface adhesion, accordingly contributing to ensuing colonization. Increasing ionic strength (1-100 mM) further stimulated initial colonization associated with compressed electrical double layer and decreased electrokinetic potential that reduced the energy barriers for bacterial cells. These findings reveal that early biofilm development is a pipe material and roughness-controlled process, which provide new insights into the mechanistic understanding of the ever-growing biofilms in drinking water systems.

为探究饮用水中消毒剂对细菌在管材粗糙表面上附着行为的影响机制,探讨了消毒剂条件下细菌在不同类型、不同粗糙程度管材上的附着行为,并借助于基于表面热力学的 XDLVO(extended-Derjaguin-Landau-Verwey-Overbeek)理论解析细菌与粗糙表面的交互作用过程.结果表明,投加氯(≤1.0mg/L)明显促进了细菌在管材表面的附着(相较于未投加时扩大 4∼6 倍),且细菌更倾向于在塑料管材表面定殖,增大管材表面粗糙度进一步促进了细菌的附着.基于XDLVO理论解析表明,1.0mg/L氯提高了细菌与管材表面间的酸碱作用项和范德华作用项,进而促进细菌的表面附着行为;而增大管材表面粗糙程度进一步强化了这一交互过程.相较于不锈钢管材,聚氯乙烯和聚乙烯管材促进了其与细菌表面的交互吸引作用能,特别在 1.0mg/L 氯条件下管材与细菌的相互作用能增加了4∼6倍,进而有助于细菌的表面附着聚集.

Anaerobic digestion following a variety of pretreatments is a promising technique for the reduction of excess sludge in municipal wastewater treatment plants (MWWTPs), and eliminations of possible pathogens, viruses, protozoa, and other disease-causing organisms. Notwithstanding a rapidly increasing health concern of antibiotic resistant bacteria (ARB) in MWWTPs, dissemination risks of ARB in anaerobic digestion processes are still poorly understood, especially in the digested supernatant. Taking the representative ARB with respect to the common tetracycline-, sulfamethoxazole-, clindamycin- and ciprofloxacin resistance, we investigated the compositions of ARB in the sludge and supernatant, and quantified their variations along the entire anaerobic sludge digestion process following ultrasonication-, alkali-hydrolysis- and alkali-ultrasonication pretreatments, respectively. Results showed that the abundance of ARB was diminished by up to 90% from the sludge along anaerobic digestion coupling with the pretreatments. Surprisingly, pretreatments clearly boosted the abundance of specific ARB (e.g., 2.3 × 102 CFU/mL of tetracycline-resistant bacteria) in the supernatant that otherwise remained relatively low value of 0.6 × 102 CFU/mL from the direct digestion. Measurements of the soluble-, loosely-bound- and tightly-bound extracellular polymeric substances components revealed a gradually intensified destruction of the sludge aggregates along the entire anaerobic digestion processes, which could be likely responsible to the increase of the ARB abundance in the supernatant. Furthermore, analysis of the bacterial community components showed that the ARB populations were strongly correlated with the occurrence of Bacteroidetes, Patescibacteria, and Tenericutes. Interestingly, intensified conjugal transfer (0.015) of antibiotic resistance genes (ARGs) was observed upon returning of the digested supernatant to the biological treatment system. It implies the likelihood of ARGs spreading and subsequent ecological risks upon anaerobic digestion towards reducing excess sludge, and therefore requires further attentions for the excess sludge treatments especially of supernatant.

Microalgal cell attaching and biofilm formation are critical in the application of microalgal biocathode, which severs as one of the hopeful candidates to an original cathode in bioelectrochemical systems. Many efforts have been put in biofilm formation and bioelectrochemical systems for years, but the predominant factors shaping microalgal biocathode formation are sketchy. We launched a pair of researches to investigate microalgal attachment and biofilm formation in the presence/absence of applied voltages using Chlamydomonas microsphaera as a model unicellular motile microalga. In this study, we presented how microalga attached and biofilm formed on a carbon felt surface without applied voltages and try to manifest the most important aspects in this process. Results showed that while nutrient sources did not directly regulate cell attachment onto the carbon felt, limited initial nutrient concentration nevertheless promoted cell attachment. Specifically, nutrient availability did not influence the early stage (20-60 min) of microalgal cell attachment but did significantly impact cell attachment during later stages (240-720 min). Further analysis revealed that nutrient availability-mediated chemotactic movements and zeta potential are crucial to facilitate the initial attachment and subsequent biofilm formation of C. microsphaera onto the surfaces, serving as an important factor controlling microalgal surface attachment. Our results demonstrate that nutrient availability is a dominant factor controlling microalgal surface attachment and subsequent biofilm formation processes. This study provides a mechanistic understanding of microalgal surface attachment and biofilm formation processes on carbon felts surfaces in the absence of applied voltages.

针对目前有关消毒剂胁迫下颗粒物对微生物保护作用机制尚不清晰,以饮用水中微生物为研究对象,通过构建静态模拟实验装置,解析消毒剂胁迫下针铁矿对微生物聚集和消毒效果的影响机制.结果表明,当未投加消毒剂氯时,针铁矿浓度对水中微生物失活率基本没有影响;而当有氯存在时,针铁矿促进氯的衰减、微生物胞外聚合物的分泌以及其聚集行为,进而增强其抵抗消毒剂灭活的能力,尤其在0.5mg/L氯时,其保护效果较为显著.

Drought loss risk curves can quantitatively assess regional drought and indicate the mechanism of drought hazards. In this study, the drought events were identified using the run theory based on Standard Precipitation Index (SPI) and Composite meteorological drought Index (CI) separately calculated by daily weather data during 1955–2012. The frequency of drought events was calculated by using the Copula function. The yield loss of soybeans under different irrigation levels in dry years was simulated by DSSAT-CROPGRO-soybean model. Finally, the regional drought risk for soybeans in Bengbu city was analyzed by constructing a series of relationship curves among the drought frequency, soybean drought loss, and the irrigation level. The results indicated that (1) both the SPI and CI were applicable to identifying drought events in the selected city, but SPI was more sensitive in identifying short-term drought events, and CI was more reliable in recognizing medium-term drought events. (2) The frequency of drought events during the target crop's growing period and the corresponding yield loss rate satisfied the semi-logarithmic function, and the average values of their determinant coefficients were 0.68 and 0.74 based on SPI and CI, respectively. (3) Irrigation could significantly reduce soybean yield loss in non-extreme drought events. Therefore, drought loss risk curves can reflect regional drought risk more quantitatively and facilitate the assessment and management of regional drought risk.