ABSTRACT This study evaluates the efficiency of municipal wastewater (MW)–based microalgae cultivation for biofuel production and wastewater treatment using a meta‐analysis with random resampling and bias‐corrected adjustments. Integrated systems achieved mean removal rates of 87.7% for total nitrogen, 86.2% for ammonium, 84.8% for total phosphorus and 81.5% for phosphate, with lower efficiencies for chemical oxygen demand (64.2%) and nitrate (75.3%). Biodiesel conversion efficiencies ranged from 12.4% to 97.5%, averaging 59.2% (95% CI: [43.3, 73.1]), whereas lipid content varied from 2.7% to 61.7%, averaging 29.1% [26.0, 32.1]. Mixotrophic cultivation and pretreated MW performed best under optimal conditions (22°C–25°C, high nutrient availability, low metal concentrations), whereas stress conditions enhanced lipid accumulation. However, most studies remain laboratory‐scale, limiting real‐world applicability. Key scale‐up challenges include wastewater pretreatment, cultivation strategy, environmental stability, biomass harvesting and process integration. Addressing these challenges requires urgent full‐scale validation in operational wastewater treatment plants.

ABSTRACT Water–energy–food (WEF) nexus is a complex system concerning complicated interrelations and interactions among water, energy and food sectors. Identification of the key elements among the system is significant for understanding the working mechanism of the WEF and a critical step when modelling the nexus. This study proposed a framework with the aim to find the most important variables in the WEF by coupling system dynamics and network analysis (NA). First, the system elements of the nexus and their interconnections are qualitatively analysed using the causal‐loop diagram of the system dynamics model. The diagram is then transferred as a network in which the system elements and associated connections are treated as nodes and edges of the network, respectively. The NA is then applied to the network, and attributes of the nodes such as degree, betweenness and closeness centrality are investigated. The importance of the elements is assigned based on those attributes valuations, and the key system elements are identified using multi‐attribute decision approach. Two scales of WEF, for example, global and household, are used as case studies. The results showed that the proposed approach effectively identified the key elements of the two WEFs and prioritized the system elements based on their importance. The proposed approach can be applied to help police makers gain understanding of the complexity of the WEF and to provide a vital reference of the modelling setup when simulating the nexus.

ABSTRACT This study aimed to isolate and characterize biodegrading Mycobacterium strains from refinery‐contaminated soils and evaluate their interactions with environmental pollutants and their potential in enhancing soil quality. Thirty‐six soil samples were analyzed to isolate the PAH/heavy metal biodegrading mycobacteria. Soil quality parameters and barley growth indices were evaluated to determine ecological impacts after bioremediation. From 36 samples, 13 (36.11%) Mycobacterium isolates were identified. Among this, M. austroafricanum 3 isolates (23.07%), M. chubuense and M. celeriflavum 2 isolates (15.38%) were the prevalent species. CFU ranged from 1.0 × 10 4 to 2.0 × 10 6 /while TPH, PAHs and heavy metals were measured at 120–8500, 10–350 and 15–120 mg/kg, respectively. Mycobacterium gilvum and Mycobacterium smegmatis exhibited > 60% degradation of both PAHs and heavy metals, while Mycobacterium austroafricanum and Mycobacterium vaccae primarily degraded PAHs, and Megalaima franklinii and M. houstonense were effective in reducing heavy metals. M. gilvum significantly enhanced barley growth ( p < 0.05), whereas Mycobacterium chubuense had minimal impact. These findings highlight the potential of indigenous Mycobacterium species as an effective approach for bioremediation and soil restoration.

ABSTRACT Based on the Chinese context, this study uses evolutionary game theory to analyse the factors affecting rural water supply security, modelling regulators, water suppliers and farmers as players to explore the feasibility of effective cooperation mechanisms. Key findings include the following: (1) Eight stable equilibrium strategies exist under certain conditions. (2) Increased net benefits from active regulation lead regulators to enforce rules more rigorously, with higher penalties enhancing their willingness. (3) Water suppliers are more likely to adopt stringent safety measures when the benefits of providing safe water increase, thereby reducing the need for regulatory intervention. (4) Farmers are more inclined to monitor water quality when participation benefits increase, prompting utilities to enhance safety. Therefore, policymakers should strengthen regulatory frameworks to encourage stakeholder participation and establish effective communication and collaboration mechanisms. This study's novelty lies in applying evolutionary game theory to multi‐stakeholder interactions in rural water supply, promoting cooperation and improving management strategies.

ABSTRACT In the relentless battle for survival, Salmonella has evolved mechanisms to withstand harsh conditions such as extreme temperatures, fluctuating pH, oxidative stress and disinfectants, which often exist in aquatic environments. Among these survival mechanisms, the viable but nonculturable (VBNC) state stands out as a major threat to water safety as well as public health. Although alive and metabolically active, bacteria in a VBNC state defy growth on standard culture media, rendering them invisible to routine diagnostic techniques. Furthermore, bacteria in a VBNC state retain their virulence and can still cause disease and outbreaks. This review article will discuss the VBNC state of Salmonella in aquatic environments, highlight the environmental and genetic determinants of VBNC Salmonella , as well as discuss available methods for detecting viable as well as VBNC Salmonella in environmental samples, including the role of artificial intelligence in facilitating rapid and accurate detection of viable and non‐viable bacterial cells.

ABSTRACT This study applies response surface methodology to optimize the experimental conditions for ultrasound‐assisted extraction of the active component from Saudi Khenaizi date seeds. The effectiveness of the extraction was evaluated through the coagulation process using synthetic wastewater, focusing on colour and turbidity removal efficiencies. A three‐factor (temperature, sonication time, and solvent concentration) with three levels Box–Behnken design was employed. The results revealed that sonication temperature and solvent concentration were the primary factors influencing the recovery of the active ingredient. Additionally, these factors significantly influenced the removal efficiencies ( p ‐value < 0.05). While the interaction between factors was not significant when NaCl solvent was used, the interactions between temperature and sonication time, as well as sonication time and solvent concentration, were significant when NaOH solvent was employed. The quadratic models demonstrated reasonable prediction capability for the experimental values, with R 2 values of 87.33% and 98.65% for colour and turbidity responses using NaCl solvent and 98.37% and 95.89% when NaOH was employed. Furthermore, the optimum conditions for the extraction process using each solvent were determined and experimentally validated. NaCl was found to be more favourable for turbidity removal (89.39% removal efficiency), while NaOH was more favourable for colour removal (70.95% removal efficiency). The findings of this study highlight the importance of optimizing natural coagulant extraction processes. By developing sustainable methods for wastewater treatment, this research offers valuable solutions that can be applied globally, contributing to environmental conservation and resource efficiency.

ABSTRACT Sequencing batch reactors (SBRs) are systems that are used in municipal wastewater treatment that maintain consistent performance, even under varying organic shock loading (OSL). This study analyzes the application of machine learning (ML) with STOAT software simulations to improve SBR performance by predicting effluent quality under flocculating OSL scenarios. Comparative analysis was carried out using ML models and STOAT software simulations to evaluate their efficiency. The first tests revealed that the 2× and 1.6× applied loads exceeded effluent environmental requirements; therefore, OSL was reduced to 1.3× of the influent organic load that complied with the environmental limits. Both ML models and STOAT software simulations results were closely aligned; this shows that these methods are effective for predicting SBR WWTP performance with minimal effort and no cost. These results highlight that ML models and STOAT software can be practical tools for reducing operational risk and improving decision‐making when varying OSL conditions.

ABSTRACT Exploring the effect of distance on residents' willingness to pay (WTP) for river protection is important for policymaking and cost‐sharing. However, the literature lacks attention to the spatial characteristics of rivers. The mechanism of various factors at different distances influencing respondents' WTP needs further exploration. This study used a double‐bounded dichotomous choice framework and face‐to‐face interviews with residents in the Songhua River Basin. By constructing the contoured WTP model, the influence mechanism of distance on WTP in different contoured regions is explored, and the mean WTP is 179.79, 127.92 and 107.56 CNY per year, respectively. The paired t test reveals differences between each contoured region's mean WTP, verifying the distance decay. The influence mechanisms of WTP vary with distance. As the distance increases, the influence of distance variables on WTP decreases, and the role of socioeconomic variables is enhanced.

ABSTRACT The treatment and reuse of wastewater are vital tools for managing water resources, with public acceptability being crucial for their success. This study reviews public perceptions and acceptance of treated wastewater reuse, identifying key factors and engagement strategies. A systematic review of selected articles from databases was conducted, using the KH Coder software for text mining and network analysis to uncover themes and connections. Results indicate substantial public support, particularly for indirect reuse, but beliefs and a lack of awareness significantly impact acceptance. Effective engagement strategies must include safety assurances, educational campaigns, economic incentives, and public participation. Clear communication, specific regulations, and segregated water networks are essential for the successful adoption of treated wastewater reuse.