Search

Globalization has led to a rapid rise in energy consumption, making climate change one of the world's most pressing issues. As wastewater treatment plants (WWTPs) contribute to climate change by emitting greenhouse gases (GHGs), this study estimated the total GHG emissions of WWTPs by classifying them as either direct or indirect carbon emissions. The effectiveness of the use of solar photovoltaic systems and biogas produced by WWTPs in increasing energy recovery and reducing GHG emissions was investigated. This study demonstrated that the use of an up-flow anaerobic sludge blanket (UASB) reactor with a biogas flow of 9 120.77 m3/d and an activated sludge processing system (ASPS) reactor with a biogas flow of 14 004 m3/d, in addition to the energy production from the UASB reactor (6 421.8 MW⸱h per year) and the ASPS reactor (9 860.0 MW⸱h per year), yielded a reduction of 3 316.85 and 5 092.69 t of CO2 equivalent per year, respectively. Furthermore, the co-design of wastewater processes could be utilized to optimize biogas energy recovery. Moreover, the use of solar photovoltaic systems reduced GHG emissions from WWTPs. This is important to the transition to renewable energy because it resulted in a 10%–40% reduction in carbon emissions from WWTPs. Integrating renewable energy sources, biogas, and solar energy could provide up to 88% of the annual energy requirements of WWTPs. Recommendations are provided for further research considering the limited availability of integrated resources for studying the simultaneous utilization of photovoltaic and biogas systems.

The completely autotrophic nitrogen removal over nitrite (CANON) is a new type of nitrogen removal process developed in recent years. The control of dissolved oxygen (DO) in this process is relatively stringent, especially in low-substrate wastewater treatment. However, the results of studies on the operation of the process in different aeration modes are still controversial, and investigations on biofilm type CANON reactors are limited. In this study, a pilot-scale CANON bioreactor filled with suspended carriers was investigated on the treatment of wastewater at low ammonium concentrations, and the effect of the aeration mode on autotrophic nitrogen removal was evaluated. Seven conditions with various aeration on/off times and DO levels were tested. The results showed that an intermittent aeration with a 20-min/20-min aeration on/off time and DO concentrations of 1.0–1.3 mg/L at the end of the aeration period was appropriate, potentially inhibiting nitrite oxidizing bacteria (NOB) and keeping the total nitrogen (TN) removal rate at a relatively high level of 76.7% ± 2.5%. In the optimal aeration mode, the reactor achieved effluent TN and NH4+-N concentrations of (11.1 ± 3.3) mg/L and (3.6 ± 2.3) mg/L, respectively, with a hydraulic retention time of 12 h and an influent NH4+-N concentration of (48.6 ± 9.4) mg/L at 30.1°C ± 2.2°C. The results of metagenomic sequencing for microorganisms on carriers indicated that the main nitrogen removal bacteria in the reactor were Proteobacteria, Planctomycetes, and Nitrospirae. The NOB genus Nitrospira was completely inhibited by intermittent aeration. Candidatus Kuenenia had strong adaptability to low-concentration wastewater.

Deep storage tunnels (DSTs) are used in densely urbanized areas to relieve stormwater collection systems, thereby reducing urban floods and runoff pollution, due to their substantial storage capacity. The computation of the hydraulic characteristics and flow trajectories of DSTs under rapid filling scenarios can help to predict sediment deposition and pollutant accumulation associated with the stored runoff, as well as the likelihood of operational problems, such as excessive surging. However, such assessments are complicated by various inflow scenarios encountered in tunnel systems during their operation. In this study, the Suzhou River DST in China is selected as a study case. Particles were tracked, and hydraulic analysis was conducted with scaled model experiments and numerical models. The flow field, particle movement, air‒water phase, and pressure patterns in the DST were simulated under various one- and two-sided inflow scenarios. The results showed that with regards to the design conditions involving two-sided inflows, flow reversals occurred with stepwise increases in the water surface and pressure. In contrast, this phenomenon was not observed under the one-sided inflow scenario. Under the asymmetric two-sided inflow scenarios, water inflows led to particle accumulation near the shaft, reducing the received inflows. However, under the symmetric inflow conditions, particles were concentrated near the middle of the tunnel. Compared to those under the symmetric inflow scenario, asymmetric inflow caused surface wave and entrapped air reductions. This study could provide support for regulation of the inflow of the Suzhou River DST and for prediction of sediment and pollutant accumulation.

It is necessary to treat textile effluents before discharging them into natural water bodies as they harm the environment. Compared to conventional treatment methods, catalytic ozonation has gained attention due to its effectiveness in removing refractory organic pollutants. In this study, the coprecipitation method was used to synthesize a composite metal oxide of silver and cerium oxide, and the synthesized catalyst was used to eliminate the Reactive Black 5 (RB5) dye. X-ray diffraction, scanning electron microscopic, and Brunauer–Emmett–Teller surface area analyses were performed to characterize the synthesized catalyst. Afterwards, relevant experimental parameters, such as pH, ozone and catalyst dosages, and initial dye concentration, were investigated. The experiments revealed that the optimal experimental conditions were a pH value of 10, a catalyst dosage of 0.7 g/L, and an ozone dosage of 60 L/h. In these optimized conditions, the RB5 dye was entirely removed, and a chemical oxygen demand removal efficiency of 88% was achieved within a reaction time of 80 min. Furthermore, the recycling potential of the catalyst was tested for three cycles, and no deterioration in its activity was observed. Additionally, studies were conducted using a hydroxyl radical scavenger in order to understand the reaction pathway of the system. As a result, the indirect pathway was more dominant than the direct pathway in the system.

Moistube irrigation is a new micro-irrigation technology. Accurately estimating its wetting pattern dimensions presents a challenge. Therefore, it is necessary to develop models for efficient assessment of the wetting transport pattern in order to design a cost-effective moistube irrigation system. To achieve this goal, this study developed a multivariate nonlinear regression model and compared it with a dimensional model. HYDRUS-2D was used to perform numerical simulations of 56 irrigation scenarios with different factors. The experiments showed that the shape of the wetting soil body approximated a cylinder and was mainly affected by soil texture, pressure head, and matric potential. A multivariate nonlinear model using a power function relationship between wetting size and irrigation time was developed, with a determination coefficient greater than 0.99. The model was validated for cases with six soil texture types, with mean average absolute errors of 0.43–0.90 cm, root mean square errors of 0.51–0.95 cm, and mean deviation percentage values of 3.23%–6.27%. The multivariate nonlinear regression model outperformed the dimensional model. It can therefore provide a scientific foundation for the development of moistube irrigation systems.

The Tibetan Plateau (TP) has undergone significant warming and humidification in recent years, resulting in rapid permafrost degradation and spatiotemporal variations in hydrological processes, such as subsurface water transport, hydrothermal conversion, and runoff generation. Understanding the mechanisms of hydrological processes in permafrost areas under changing climate is crucial for accurately evaluating hydrological responses on the TP. This study comprehensively discusses the permafrost hydrological processes of the TP under changing climate. Topics include climate conditions and permafrost states, subsurface water transport under freeze–thaw conditions, development of thermokarst lakes and hydrothermal processes, and runoff response during permafrost degradation. This study offers a comprehensive understanding of permafrost changes and their hydrological responses, contributing significantly to water security and sustainable development on the TP.

Of several noble metal nanoparticles, silver nanoparticles (AgNPs) have attracted special attention due to their distinct properties, such as favorable electrical conductivity, chemical stability, and catalytic and antibacterial activities. Green synthesis of AgNPs using plant extracts containing phytochemical agents has attracted considerable interest. This environmentally friendly approach is more biocompatible and cost-efficient and has the capability of supporting large-scale synthesis. This study developed an eco-friendly method for the preparation of AgNPs using the aqueous leaf extract of Saussurea obvallata as reducing and capping agents. Ultraviolet visible spectroscopy (UV–Vis), Fourier transform infrared spectroscopy (FTIR), Raman, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) analyses were conducted to characterize the synthesized AgNPs. The morphology of AgNPs was found to be spherical with an average crystallite size of 12 nm and a maximum absorbance at 410 nm. 10 mg of AgNPs had potential to reduce 4-nitrophenol to 4-aminophenol in 16 min and exhibited strong biological activities against the Gram-negative bacteria Escherichia coli (12 mm) and Gram-positive bacteria Enterococcus faecalis (13 mm). The antioxidant activity of the synthesized AgNPs was investigated against the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and exhibited up to 61.21% ± 0.02% at an AgNPs concentration of 500 μg/mL.

This study synthesized a ferric oxide–nanographite (NG) nanocomposite (Fe2O3@NG) from waste toner powder through carbonization. Subsequently, a TiO2/Fe2O3@NG nanohybrid was fabricated using the sol–gel technique to improve the photocatalytic degradation of dyes. TiO2/Fe2O3@NG nanocomposites were prepared at TiO2:Fe2O3@NG ratios of 2:1 (Ti:T-21), 1:1 (Ti:T-11), and 1:2 (Ti:T-12). The porosity, morphology, surface chemistry, and chemical interactions between TiO2, Fe2O3, and graphite in the prepared TiO2/Fe2O3@NG nanocomposites were characterized using the Brunauer–Emmett–Teller (BET) method and microscopic and spectroscopic analyses. The TiO2/Fe2O3@NG nanohybrid exhibited a reduced bandgap (2.4–2.9 eV) and enhanced charge carrier separation through charge transfer at the junction of the hetero-structured TiO2/Fe2O3@NG nanohybrid. Preliminary experiments revealed that Ti:T-21 was the most effective photocatalyst for degrading acid blue-25 (AB-25) compared to Ti:T-11, Ti:T-12, sole TiO2, and Fe2O3@NG. This study also investigated the impacts of catalyst dose and initial dye concentration on the AB-25 photocatalytic degradation. Notably, 97% of 5-mg/L AB-25 was removed using 1.25-g/L Ti:T-21 at an unmodified pH of 6.4 within 120 min. Furthermore, Ti:T-21 exhibited remarkable recyclability in its immobilized form, achieving degradation ratios of 74.7%–71.8% over five consecutive runs, compared to removal efficiencies of 85.0%–62.3% in the suspended mode. Trapping experiments identified hydroxyl radicals, holes, and superoxide as the principal reactive radicals. The TiO2/Fe2O3@NG/light system was effective in disintegrating and mineralizing other synthetic dyes such as Congo red, methylene blue, and methyl red, indicating its potential for industrial-scale degradation of authentic dye wastewater. The utilization of waste toner for water treatment is highlighted as a strategy to promote environmental sustainability, foster a circular economy, and contribute to pollution remediation.

Nano zero-valent iron (nZVI) and sulfidation-modified nZVI (S-nZVI) were synthesized and used to remove hexavalent chromium (Cr(VI)) in wastewater. Characterization of the products showed that the sulfidation process significantly changed the morphology of nZVI, with enhanced crystallinity. The effects of S/Fe ratio, pH value, and reaction temperature on Cr(VI) removal were studied. A S/Fe ratio of 0.5 was the most appropriate parameter, with a removal efficiency of 98% in the condition of pH = 2. The effects of anions (Cl−, NO3−, CO32−, and SO42−) and cations (Ca2+ and Mg2+) on the Cr(VI) removal efficiency were investigated, and the relevant mechanisms were discussed. The Cr(VI) removal efficiency of S-nZVI was significantly greater than that of nZVI, mainly owing to the existence of FeS layers that could protect Fe0 cores and prompt electron transfer. The aging and cycling experiments showed that S-nZVI could maintain its reactivity when facing the corrosion of water, and showed cycling stability. Thus, S-nZVI is an effective and feasible agent for the remediation of Cr(VI)-contained wastewater.

The offshore renewable energy industry has been developing farms of floating offshore wind turbines in water depths up to 100 m. In Vietnam, floating offshore wind turbines have been developed to increase the production of clean and sustainable energy. The mooring system, which is used to keep the turbine stable and ensure the safety and economic efficiency of wind power production, is an important part of a floating offshore wind turbine. Appropriate selection of the mooring type and mooring line material can reduce the risks arising from the motion of wind turbines. Different types of mooring line material have been simulated and compared in order to determine the optimal type with the minimum motion risk for a floating wind turbine. This study focused on numerical modeling of semi-taut mooring systems using nonlinear materials for a semi-submersible wind turbine. Several modeling approaches common to current practice were applied. Hydrodynamic analysis was performed to investigate the motion of the response amplitude operators of the floating wind turbine. Dynamic analysis of mooring systems was performed using a time domain to obtain the tension responses of mooring lines under the ultimate limit states and fatigue limit states in Vietnamese sea conditions. The results showed that the use of nonlinear materials (polyester and/or nylon) for mooring systems can minimize the movement of the turbine and save costs. The use of synthetic fibers can reduce the maximum tension in mooring lines and the length of mooring lines. However, synthetic fiber ropes showed highly nonlinear load elongation properties, which were difficult to simulate using numerical software. The comparison of the characteristics of polyester and nylon mooring lines showed that the maximum and mean tensions of the nylon line were less than those of the polyester line. In addition, the un-stretched length of the polyester line was greater than that of the nylon line under the same mean tension load. Therefore, nylon material is recommended for the mooring lines of a floating offshore wind turbine.

Water covers most of the Earth’s surface and is nowhere near a good ecological or recreational state in many areas of the world. Moreover, only a small fraction of the water is potable. As climate change-induced extreme weather events become ever more prevalent, more and more issues arise, such as worsening water quality problems. Therefore, protecting invaluable and useable drinking water is critical. Environmental agencies must continuously check water sources to determine whether they are in a good or healthy state regarding pollutant levels and ecological status. The currently available tools are better suited for stationary laboratory use, and domain specialists lack suitable tools for on-site visualisation and interactive exploration of environmental data. Meanwhile, data collection for laboratory analysis requires substantial time and significant effort. We, therefore, developed an augmented reality system with a Microsoft HoloLens 2 device to explore the visualisation of water quality and status in situ. The developed prototype visualises geo-referenced sensor measurements incorporated into the perspective of the surroundings. Any users interested in water bodies’ conditions can quickly examine and retrieve an overview of water body status using augmented reality and then take necessary steps to address the current situation.

Harmful algal blooms (HABs) resulting from eutrophication pose a major threat to ecosystems and human health, necessitating effective control measures. Allelochemicals have shown their importance in slowing down algal proliferation due to their proven efficacy and low ecological impacts. In this study, allelopathy tea polyphenols (TPs) and β-cyclodextrin were combined to prepare slow-release algicidal microcapsules, and the diversity of microbial community in the algal inhibition process was analyzed. Results showed that TP slow-release microcapsules had strong algicidal activity. When against Microcystis aeruginosa within 20 d, their constant inhibitory rate was up to 99% compared to the control group. Microbial diversity decreased with an increase in algae density, and the species richness and diversity of algae increased under the stress of TP slow-release microcapsules. The redundancy analysis showed that the environmental factors with impacts on the abundance and diversity of bacterial communities in descending order were dissolved oxygen, pH, and temperature. This study provides a theoretical basis for the application of TP slow-release microcapsules to actual water.

The crop water stress index (CWSI) is an important technique for determining stress levels in the plant and directing irrigation management techniques. To determine the CWSI for sunflower, a pot-based research trial was carried out in the research field of the Department of Soil and Water Engineering, PAU, Ludhiana (India) during the summer of 2023. The sensor-based irrigation scheduling was carried out on the basis of the depletion of total available soil moisture (TASM). The drip irrigation treatments consist of I1 (full irrigation), I2 (20% depletion of TASM), and I3 (40% depletion of TASM). The results revealed that the highest amount of water applied under I1 was recorded at 484.4 mm, while I2 (387.5 mm) and I3 (290.7 mm) during the growing season of sunflower. The results revealed that for kernel diameter and seed weight, I1 and I2 were statistically non-significant to each other while I1 and I3 were statistically significant to each other. The highest water productivity recorded for I2, followed by I3. The overall findings revealed that an average CWSI value of 0.85 for the sunflower crop falls within the range of lower and upper baselines. The response of physico-chemical properties of sunflower seeds showed a high correlation with the draught condition. HIGHLIGHTS Investigated crop water stress (CWSI) of sunflower under varying soil moisture depletion.; To develop lower and upper limits of baselines for fully irrigated and under stressed conditions.; To analyse physico-chemical changes of sunflower seed and oil.; To develop sensor-based irrigation scheduling for sunflower crops under deficit condition.; To analyse the water productivity of sunflower under various irrigation regimes.;

The layout of emergency monitoring points (EMPs) in water distribution networks is one of the main measures to ensure the water safety of residents and preserve the sustainable development of cities and society. The impact factors on the layout of EMPs are first analyzed. Then, a new emergency monitoring layout model is presented with the goal of maximizing the number of the excluded possible sources and minimizing the formulated time of emergency response. Finally, taking EPANET Network 3 as a simulation case to verify the proposed model. The results show the new layout model can effectively exclude 60% of the number of possible sources, and shorten 18% of the formulated time of emergency response measure. There are many factors that affect the layout of EMPs, which mainly include the time of arranging EMPs, the latest time to formulate the emergency response measure, the number of emergency monitoring equipment available, and the relative error criteria of pollutant concentration, from apparently to slightly. It provides a new idea for emergency decision-makers to deal with sudden water pollution accidents in water distribution networks. HIGHLIGHTS A new emergency monitoring layout model (EMLM) is proposed for the water distribution network.; The emergency monitoring points (EMPs) layout problem is addressed as a multi-objective optimization problem.; The goal of new EMLM is to maximize the excluded possible sources and minimize emergency response time.; The factors that affect the locations and numbers of EMPs are analyzed, and the influence of each factor is ranked.;

This study delves into the analysis of recession characteristics of spring base flow, focusing on the Hill campus spring (elevation of approximately 2,150 m) and Fakua spring (elevation of approximately 1,850 m) in the Tehri Garhwal district of Uttarakhand, India. Spanning from January 1999 to December 2004, discharge data from G.B. Pant University of Agriculture and Technology's Hill campus are employed. The research employs an automated, objective-based method to generate master recession curves (MRCs) and categorize them into early, intermittent, and late recession segments. Statistical parameters and low-flow indices from flow duration curves (FDCs) are utilized for flow assessment, while base flow indices (BFIs) are analyzed using the Web-based Hydrograph Analysis Tool (WHAT). The findings highlight the importance of water storage strategies during the rainy season for the sustainable utilization of spring water. The study suggests that the techniques applied are equally applicable for analyzing river flow recession characteristics, emphasizing the broader implications for integrated water resources planning and management in mountainous regions. HIGHLIGHTS This study presents a novel automated and objective-driven method for generating master recession curves (MRCs).; It categorizes them into early, intermittent, and late recession segments.; This method employs statistical parameters and low-flow indices derived from flow duration curves (FDCs).;

A curved channel is a common flow form in nature, often hosting aquatic vegetation along rivers. The stem thickness of this vegetation affects its resistance to flow and subsequently influences flow characteristics. To explore the impact of stem thickness on river flow in curved channels, we developed a Reynolds stress model based on real river flow conditions and vegetation data. The flow characteristics were analyzed in terms of flow velocity, Reynolds stress and turbulence intensity by varying the stem thickness of the vegetation in the vegetated area. The results of the study reveal that: (1) Water velocity in the vegetated area is significantly reduced compared to the non-vegetated area, with a greater reduction observed for thicker stems. Increasing the vegetation diameter by 3 mm resulted in a velocity decrease of 2.31–26.55%. (2) Thicker vegetation stems lead to more intense energy exchange in water flow. A 3 mm increase in vegetation diameter increased Reynolds stress by 91.81–139.70%. (3) Turbulent kinetic energy in the vegetated area is significantly higher than in the non-vegetated area, with greater turbulence intensity observed for thicker vegetation stems. Increasing the vegetation diameter by 3 mm resulted in a turbulent kinetic energy increase of 115.19–218.55%. HIGHLIGHTS Less research has been done on the effect of vegetation stem thickness on water flow in curved channels.; The feasibility of studying the flow characteristics of curved river channels through simulation is verified.; Analysis of sedimentation by comparing concave and convex shores.; The results can guide the construction of river channels and the design of aquatic systems.; It can provide relevant data for the subsequent research on the influence of vegetation stem coarseness on water flow characteristics.;

Urban water demand prediction is not only the foundation of water resource planning and management, but also an important component of water supply system optimization and scheduling. Therefore, predicting future water demand is of great significance. For univariate time series data, the issue of outliers can be solved through data preprocessing. Then, the data input dimension is increased through feature engineering, and finally, the LightGBM (Light Gradient Boosting Machine) model is used to predict future water demand. The results demonstrate that cubic polynomial interpolation outperforms the Prophet model and the linear method in the context of missing value interpolation tasks. In terms of predicting water demand, the LightGBM model demonstrates excellent forecasting performance and can effectively predict future water demand trends. The evaluation indicators MAPE (mean absolute percentage error) and NSE (Nash–Sutcliffe efficiency coefficient) on the test dataset are 4.28% and 0.94, respectively. These indicators can provide a scientific basis for short-term prediction of water supply enterprises. HIGHLIGHTS Interpolation of raw training data may not necessarily improve the performance of predictive models.; Accurate prediction of univariate data can be achieved through feature engineering and machine learning.;

Deteriorating water quality poses a substantial risk to human health, with billions at risk of waterborne diseases due to contamination. Insufficient water quality data augment risks as conventional monitoring methods lack comprehensive coverage. Technologies like the Internet of Things and machine learning offer real-time water quality monitoring and classification. IoT nodes often provide point data insufficient for monitoring the quality of entire water bodies. Remote sensing, though useful, has limitations such as measuring only optically active parameters and being affected by climate and resolution issues. To address these challenges, an unmanned surface vehicle named `AquaDrone' has been developed. AquaDrone traverses water bodies, collecting data of four key parameters (pH, dissolved oxygen, electrical conductivity, and temperature) along with GPS coordinates. The data is transmitted to a web portal via LoRa communication and Wi-Fi, where visualizations like data tables, trendlines and color-coded heatmaps are generated. A multilayer perceptron classifies water quality into five categories, aiding in real-time classification. A comparative analysis of various oversampling techniques has been conducted in the context of water quality classification. The AquaDrone offers a feasible solution for monitoring quality of small to medium-sized water bodies, crucial for safeguarding public health. HIGHLIGHTS AquaDrone measures four physicochemical parameters of water along with GPS coordinates to monitor water quality in real-time.; A multilayer perceptron classifies water quality into five categories, with oversampling used to enhance model training.; AquaDrone wirelessly transmits data to the web portal, where trendlines, data table and a color-coded heatmap are generated to visualize water quality.; This ensures effective real-time monitoring in small to medium-sized water bodies, protecting both water sources and human health.;

The present investigation focuses on using commercially available MF, UF, and NF membranes to eliminate Fe from real groundwater. The impact of process parameters, including applied pressure, temperature, pH, time, and concentration, on flux and Fe removal% is investigated. Results of the permeation test confirm higher permeability for MF membranes (214.71 L/m2.h.bar) than that for NF (2.708 L/m2.h.bar) and UF (56.52 L/m2.h.bar) membranes. The FESEM-EDS characterization confirms the deposition of dominant foulant Fe particles over the membrane surface. At 2 bar applied pressure (temperature = 30 °C, pH = 6.13, and concentration = 6.62 ppm), MF, UF, and NF can eliminate 93.5, 90.2, and 100% Fe, respectively. However, UF and NF exhibit much lower fluxes (72.43 and 3.85 L/m2.h, respectively) compared to MF (317.13 L/m2.h) at the same process conditions. NF eliminates 100% Fe from start to end with rising pressure, while MF (62.16–100) and UF (87.09–100) show gradually improved removal rates. Above pH 6, all membranes demonstrate higher Fe rejection because the oxidation rate of ferrous iron increases at a high pH. With increasing concentration (6–500 ppm), Fe removal efficiency increases for NF (88.26–94.18%) but decreases for both MF (89.63–23.64%) and UF (27.66–14.4%). To validate experimental findings, five machine learning (ML) regression models are scrutinized using various statistical measures. HIGHLIGHTS Treatment of highly Fe-contaminated real groundwater by MF, UF, and NF flat sheet membranes.; MF shows much higher flux (317.13 L/m2.h) and 100% Fe removal, and is the best membrane.; FESEM-EDS confirms the deposition of dominant foulant Fe over membrane surfaces.; Effects of pressure, pH, temperature, time, and concentration on flux and Fe removal are demonstrated.; Machine learning effectively legitimates the experimental data with fewer errors.;

The paper analyses the spatial and temporal characteristics of extreme precipitation in the upper reaches of the Yangtze River through extreme precipitation indicators based on the trend method, the Mann–Kendall trend test, and the rescaled extreme deviation extreme deviation using daily precipitation data from 1961 to 2021. The following conclusions were obtained: The overall precipitation in the upper reaches of the Yangtze River is reduced, and the number of rainy days is reduced. The frequency of extreme precipitation is generally reduced, but the spatial difference in the intensity of extreme precipitation is greater, which makes the occurrence of extreme precipitation more concentrated and more destructive. Extreme precipitation indicators showed relatively large fluctuations after 2000, especially in terms of extreme precipitation intensity. The frequency of extreme precipitation in the upper reaches of the Yangtze River is the highest in the main stream of the Yangtze River Basin and the Wujiang River Basin, the intensity of extreme precipitation is in the Jialing River and the Wujiang River Basin, and the accumulation of extreme precipitation is the highest in the Jialing River and the Wujiang River Basin, whereas the maximum value of the station extreme precipitation intensity and frequency is in the Minjiang River Basin. HIGHLIGHTS The overall extreme precipitation characteristics of the upper reaches of the Yangtze River under climate change were analysed.; Differences in extreme precipitation characteristics of the first-tier tributaries of the upper Yangtze River were analysed.; Changes in water resources in the upper reaches of the Yangtze River have a major impact on China's economy, food security, and energy resources.;

The current study aimed to investigate the effect of planting date and irrigation on some characteristics of cumin cultivated in Iran. The experimental characteristics included three planting dates and five irrigation regimes. Irrigation at flowering + seed filling stage and full irrigation had the highest essential oil content (3.6%) and plant height (16.71 cm), respectively. On all planting dates, irrigation enhanced the total chlorophyll and carotenoids content, relative water content, umbel number plant−1, seed number umbel−1, 1,000-seed weight, and seed yield but reduced the proline content and water-use efficiency (WUE). The highest chlorophyll content (1.54 mg g−1 fresh weight (FW)), carotenoids content (0.35 mg g−1 FW), umbel number plant−1 (18.03), seed number umbel−1 (21.16), 1,000-seed weight (4.12 g), seed yield (1002.7 kg ha−1), and essential oil yield (22.13 kg ha−1) were obtained on 19 January and irrigation at the flowering + seed filling stages. The greatest amount of WUE (0.53 kg m−3) was measured on 9 January under no irrigation condition. Therefore, to produce cumin under similar climatic conditions, early planting of cumin in early January, along with two irrigations at the flowering and seed filling stages, is recommended. HIGHLIGHTS Changing the plant growth conditions changes the morphological and physiological characteristics.; Delay in cumin planting reduced the carotenoids content.; By balancing redox reactions, proline induces cellular homeostasis and reduces lipid peroxidation.; The water deficit caused the remarkable accumulation of secondary metabolites.;

Water distribution networks (WDNs) are critical infrastructures prone to vulnerabilities which lead to failures. Identifying vulnerable components, especially multiple pipe failure combinations, is crucial for effective management and ensuring high reliability. Hydraulic simulations are commonly used for analysing the criticality of WDN, but are time-consuming and highly data-reliant, limiting the number of testable combinations. To address these limitations and constraints, a graph-based method is proposed to quantify the impact magnitude of multiple pipe failure scenarios on performance, enabling the identification of critical combinations. The proposed graph-based approach utilizes structural and topological characteristics of WDNs as well as spatial demand distribution to replicate hydraulic behaviour. The accuracy of the approach is assessed by testing it on three case studies with various pipe failure combinations, and the results are compared with hydraulic analyses. The results demonstrate a strong correlation (Spearman coefficient > 0.75) between graph-based ranking and state-of-the-art hydraulic-based ranking. Additionally, the method exhibits a significant computational gain factor of greater than 30 compared with the hydraulic-based method, rendering it valuable for actively exploring a wide range of critical pipe failure combinations and devising countermeasures. Furthermore, a hybrid-based method that integrates both the graph and hydraulic-based methods is proposed for enhanced accuracy and robust assessments. HIGHLIGHTS An innovative graph-based ranking method for fast and accurate pipe criticality analysis is developed.; The results show a high correlation with the hydraulic-based ranking method with a computational gain factor of more than 30.; A hybrid-based ranking method is presented, combining the advantages of two approaches to address the limitations of the graph-based ranking method and robust assessment of the impact.;

In arid regions, the optimal utilization of river channels to collect rainwater resources can effectively alleviate the problem of water scarcity. This paper employs visual MODFLOW software to simulate the infiltration volume of rainwater under different schemes, with the objective of identifying the optimal infiltration volume. The results indicate that the infiltration volume of rainwater is 0.6, 79.7, 36.5, 62, and 10,000 m3 under different design schemes. COMSOL software is employed to simulate the infiltration situation of rainwater under different schemes, and the scheme with the most favourable infiltration effect is identified. The simulation results indicate that scenarios 2, 4, and 5 demonstrate superior early-stage infiltration performance. Ultimately, the optimal infiltration scheme is selected by integrating the infiltration volume, infiltration effect, construction, economic, and ecological factors to achieve the objective of enhancing rainwater harvesting and utilization. This study offers effective and reasonable measures for addressing the challenge of water resources management in arid regions. It provides suitable reference schemes for river channel rainwater storage projects and offers innovative approaches to rainwater resource utilization, thereby contributing to the alleviation of water scarcity in arid areas.

The demand for packaged drinking water is increasing day by day, so it is necessary that the quality of this water must be monitored. Our present study focuses on the determination of the concentration of minerals and trace elements present in commercialised packaged drinking water sold out in various regions of India. In total, we have analysed 41 brands. The different treatments through which this water has passed as claimed by the manufacturers are also mentioned. The average value of the total dissolved solids in these waters is found to be 101.1 mg L−1. The content of anions and cations present in water is represented by box and whisker plots. Bottled water samples are also analysed for the radioactive element uranium, which is observed in the range of

The study assessed static management, i.e., without planned periodic maintenance of the storage (no sediment dredging) denoted as SC1, or with maintenance denoted as SC2. The second approach was dynamic management based on applying Real-Time Control (RTC) techniques to scenario SC1 and scenario SC2 denoted as RTC-1 and RTC-2, respectively. The dynamic management of the UCT dam with RTC-1 and RTC-2 approaches increase yield by 2.1 and 1.1 ml, respectively. Additionally, RTC-1 and RTC-2 approaches increase volumetric reliability by 5.3 and 2.5%, respectively, while maintaining the required level of service of a stormwater harvesting system. SC1 and SC2 results in water savings of up to 21.15 and 21.45 ZAR/kl, respectively, while RTC-1 and RTC-2 could save up to 19.35 and 19.45 ZAR/kl. Thus, static configurations results in water savings approximately 9% in comparison to RTC. In addition, static configurations harvested stormwater at a relatively lowest unit cost in comparison to RTC configurations. Notwithstanding this finding, the RTC system exhibits a great potential in reshaping the stormwater harvesting system to simultaneously deliver water conservation and stormwater management. HIGHLIGHTS Assessed the extent to which stormwater harvesting could contribute to ‘net zero’, i.e., transitioning the University of Cape Town toward a ‘water-sensitive precinct’.; Impact of planned periodic maintenance in enhancing harvested stormwater volume.; Benefit of Real-Time Control (RTC) in enhancing harvested stormwater volume;

This study addresses the pivotal challenge of water resource allocation in urban environments by introducing a novel approach – a multi-objective chance-constrained fuzzy interval linear programming model integrated with principal component analysis (PCA). This innovative model aims to alleviate subjectivity in urban water management processes, particularly in adjusting water demands across various sectors. The proposed model incorporates correlation analysis to identify dimensionality-reducing factors of multitarget components, determining the proportion of each target component relative to the total components. Fuzzy sets are applied to irrigation water resource allocation quantity, segmented into six levels of fuzzy membership to analyze the stochasticity of water supply. Results demonstrate the model's efficacy, revealing that variations in risk probabilities impact water supply, necessitating positive water management strategies to enhance agricultural efficiency and negative strategies to mitigate the risk of inadequate water supply. Key findings emphasize the significance of agricultural water availability and the structure of irrigation water use in optimal resource allocation. Importantly, the study showcases the enhanced precision achieved through the proposed multi-objective chance-constrained fuzzy interval linear programming with PCA, thereby refining the optimization outcomes for water management under multifaceted objectives. HIGHLIGHTS Development of a multi-objective chance-constrained fuzzy interval model.; Integration principal component analysis to improve the optimal solutions.; Application of a multidimensional analysis to effectively assess risk probabilities.; Optimization of agricultural water resources under varying constraints.; Offering strategic recommendations for agricultural cropping structures.;

The assessment of the rainwater harvesting (RWH) potential in Hosaena City from medium to large public buildings is the main objective of the study. ArcGIS with Google Earth Pro was used to calculate the rooftop area of the selected building, and RWH from each category of public buildings was evaluated by considering rooftop areas, monthly rainfall, and runoff coefficient. The result shows that the highest amount of rainwater was harvested from the City Administration building in August (197.1 m3), whereas the lowest was collected from the Health Center building in December (1.8 m3). Additionally, the contribution of RWH from individual public buildings for each month was evaluated, and its values ranged from 0.073 to 1.8%. The comparison shows that Wachemo University, Nigist Eleni Comprehensive Hospital, a technical and vocational institute, and teacher training center buildings, could have a significant potential for rainwater storage, ranging from 1.56 to 28.41%. This implies that, besides saving a noteworthy volume of potable water, the excess rainwater can be stored and utilized for the later dry months. As a result, it is recommended that rooftop RWH in Hosaena be the best source of the city's water supply system to reduce the current water supply shortage. HIGHLIGHTS Rainwater harvesting (RWH) is a suitable technology to store excess rainwater and utilize it for the later dry months.; Medium to large public buildings are the main rooftop area in the field for the RWH system.; Use of RWH technology should reduce the water supply–demand gap in the city.; A large amount of rainwater per month was harvested from City Administration public buildings.;

Climate change and rainfall variability are driving many farmers to adopt irrigation, who were historically within rain-dependent regions, to sustain crop productivity. In the Mid-Atlantic region, irrigation in agriculture has grown since the 1980s due to rising temperatures and changes in precipitation patterns. Dry summers and uneven seasonal rainfall have necessitated a shift toward irrigation, particularly in Maryland's Coastal Plain. However, high dependence on confined groundwater for irrigation around this area has strained aquifers. To mitigate this strain, exploring alternative water sources is now important. This study investigates the viability of utilizing treated wastewater from plants as an irrigation substitute in Maryland's Coastal Plain. Using the Soil and Water Assessment Tool, the research evaluates crop productivity and irrigation needs under various climate scenarios. Results indicate that recycled water from nearby treatment plants can meet crop water requirements during wet years and partially during moderate and dry years, reducing aquifer reliance by 56 and 30%, respectively. This framework aims to boost yields while conserving freshwater resources. By serving as a decision support tool, stakeholders can assess the feasibility of recycled water for irrigation, thereby potentially reducing strain on confined aquifers. HIGHLIGHTS This study presents a method for utilizing reclaimed water for irrigation.; We conducted crop yield simulations for corn and soybeans, the most dominant crops in the region.; Using the SWAT model, we have calculated the water requirements for corn and soybean under various climatic conditions.; We have determined the proportion of the total water requirement that can be sourced by water reuse.;

Mixed integer linear programming (MILP) has been gaining traction as a method for solving optimal pump scheduling problems in water distribution networks (WDNs). However, inclusion of variable speed pumps (VSPs) in MILP pump scheduling frameworks has not been given adequate treatment. This article addresses this gap by describing a methodology for formulating and solving optimal pump scheduling problems with VSPs using MILP and piece-linear approximations of network components. The methodology proceeds in four steps: (a) WDN simulation with initial pump schedule(s), (b) approximation of network components, including VSP, using linear and piece-linear functions around the chosen operating points, (c) formulation of a fully parameterised mixed integer linear programme, and (d) solution of the optimisation problem and WDN simulation with optimal pump schedule(s). The methodology is coded in MATLAB/OCTAVE and Python and is publicly available on GitHub. It was applied to solve a pump scheduling problem on a two variable speed pump single-tank network that allows the reader to easily understand how the methodology works and how it is applied in practice. The results show that the formulation is robust and the optimiser is able to return a globally optimal solution for a range of operating points. HIGHLIGHTS Mathematical description of variable speed pumps (VSPs) for MILP formulations is introduced.; Formulation of pump schedule optimisations using MILP is described from first principles.; A pump scheduling framework for VSPs is designed and released as open-source software.; Problem size calculation formulae are provided for a generic network.;

As urbanisation continues to accelerate in China, the contradiction between rapid economic development and water scarcity in semi-arid cities is becoming increasingly evident. Consequently, the study of the relationship between water resources use and economic growth is of particular importance. Lanzhou City was selected as the study area, an evaluation index system was established to comprehensively evaluate the status of water resources utilisation, meanwhile, the water footprint method and Tapio decoupling model were adopted to measure the decoupling status between water utilisation and economic development from 2002 to 2021. The result showed that the total water footprint and per capita water footprint followed an increasing and then decreasing trend. The water footprint varied significantly by industrial sector, with agriculture accounting for 72.87% of total water use. The self-sufficiency rate of water resources was above 96.5%. The economic value increased substantially from 22.25 CNY/m3 in 2002 to 183.99 CNY/m3 in 2021. The water scarcity index and the pressure index were high, with annual mean values of 0.96 and 1, respectively. Water consumption and economic growth are generally decoupled weakly and strongly, with the number of strong decoupling occurrences increasing significantly from 2011 to 2021. HIGHLIGHTS In the semi-arid regions of Lanzhou City, agricultural water use was the largest flow of water resources.; To relieve stress on water resources and promote stable socio-economic development, this study combined the Tapio decoupling model to analyze the water resources.; Paths of realising sustainable water consumption while developing economy are discussed.;

A comparative assessment of water quality for drinking purposes was conducted in Ain Larbi area using the Weighted Arithmetic Water Quality Index (WA-WQI). The origin of minerals is assessed by a saturation index approach and the Gibbs diagram. Also, mineral correlation process and ion exchange mechanism are detected by the Principal Component Analysis (PCA). The PCA results indicate that the groundwater quality in the Ain Larbi study area primarily results from weathering and geochemical alteration of rock. The saturation index and Gibbs diagram support these findings. The WA-WQI was calculated for each station based on physicochemical parameters. During the wet season, three out of five classes of WQI were observed in the present study, including excellent (25%), good (70%), and poor (5%). In the dry season, the classes excellent (25%), good (30%), and poor (45%) were represented. The present situation demonstrates how hydrogeological regimes and water–rock interactions affect groundwater ion concentrations. Our results contribute to identifying drinking water requirements in the Ain Larbi region, promoting sustainable water management. HIGHLIGHTS Hydro-chemical facies for discerning the diverse nature of water.; The origin of water minerals and the geochemical processes.; Mineral correlation process and ion exchange mechanism.; Calculation for assessing the qualities of drinking water.; Water assessment in a semi-arid area.; Detecting a potential pollution.;

Due to its geographical location in the arid and semi-arid zone, Algeria is suffering from water stress amplified by the effects of climate change. For these reasons this study was conducted to evaluate the suitability for agricultural reuse of treated wastewater of Baraki WWTP. The quality for agricultural reuse is related to the physicochemical parameters and indicators of water quality. The bacteriological characteristics including total and fecal coliforms, fecal enterococci, Salmonella spp. and Staphylococcus spp. were also considered. The results revealed that SAR and SSP values were excellent for irrigation. A Wilcox diagram showed that most of the samples fell in the field of C3-S1 indicating high salinity and low sodium water. The physicochemical results indicated that most of parameters are in conformity with standards except ammonia NH4+ and total nitrogen that are higher than the permissible limit of USEPA and FAO. The average concentrations of heavy metals are low compared with the FAO recommendations. However, the bacteriological analyses confirmed the existence of germs indicating a fecal contamination exceeding the WHO regulations but an absence of pathogenic germs. Hence, the disinfection of this water and an adequate treatment is needed before its use for agricultural purposes. HIGHLIGHTS Algeria is actually facing a water crisis, especially in the agricultural sector.; Reusing treated wastewater is an alternative for irrigation.; WWTP of Baraki which uses sand filtration is a good choice for study.; The physico-chemical and bacteriological quality of the treated wastewater is poor.; Disinfection treatment is necessary for the reuse of this treated wastewater.;

Soil erosion, triggered by rainfall and runoff, poses a significant challenge for Mediterranean countries, leading to sedimentation in dam reservoirs, decreased storage capacities, and reduced agricultural fertility. Among various erosion estimation models, the RUSLE equation stands out for its consistency and minimal data requirements. The present study aims to utilize geographic information systems (GIS) software to quantify and map soil loss in the Isser watershed in northern Algeria employing the RUSLE model to strategically plan development measures and prioritize actions to safeguard high-risk erosion areas. Implementing the RUSLE-GIS approach involves integrating multiple datasets, including precipitation, soil erodibility, topography, vegetation cover, and anti-erosion practices. By combining these factors, a comprehensive map depicting erosion rates is generated. The findings categorize potential soil erosion into six groups, ranging from very low to extremely high. They indicate that 61.5% of the Isser Basin faces erosion, varying from moderate to very high (>20 t ha−1 year−1). In addition, 25% of the total surface experiences erosion levels classified as high to very high (>50 t ha−1 year−1). This underscores the urgent need for anti-erosive measures. These measures aim to safeguard the basin's soils, extend the lifespan of existing dam reservoirs (Koudiet Acerdoune and Beni Amran), and preserve their water potential. HIGHLIGHTS Use the RUSLE-GIS approach by considering all pivotal factors in water erosion processes.; Generate comprehensive factor maps for the entire watershed.; Create a geospatial potential soil erosion map.; Identify areas prone to erosion risks.; Provide a robust foundation for strategic planning to protect high-risk erosion areas, mitigate crop issues, and prolong the longevity of the existing critical dams.;

River basins receive wastewater from socio-economic activities. In such a context, a comprehensive assessment and forecast of load-bearing capacity needs to be developed. This capacity depends on many complex factors, such as hydrology, hydraulics, and environment, leading to applying a modelling approach. This study aims to propose a hybrid modelling approach to evaluate and predict the river water environmental capacity (RWEC) in a basin. Big data technology with Python is applied to process modelling results and RWEC forecasts. The long short-term memory (LSTM) model predicts RWEC on each reach of the river channel network. The {RWECP, i, P = Nitrate, BOD, Phosphate, i = hourly} data set and related factors form a time series of data used for the LSTM forecasting model. Forecast results are evaluated through the root mean square error (RMSE) and mean absolute error (MAE). The results show that the average level over all 24 reaches for 7 forecast days: RMSENitrate = 22.16 (kg/day), RMSEBOD = 38.92 (kg/day), and RMSEPhosphate = 0.79 (kg/day). This is an acceptable result for a complex system and 7-day forecast. The results of the study help significantly with pollution control. HIGHLIGHTS Suggesting steps to determine river water environmental capacity (RWEC).; Building a forecasting model based on long short-term memory (LSTM) to predict RWEC.; Assessing and forecasting RWEC for the concrete basin.; Comparing forecast accuracy by standard metric RMSE and MAE.; Clarifying RWEC dependence on hydrodynamic and environmental factors.;

Safe and reliable drinking water is essential for sustaining life. Chlorination is widely used for disinfection in water distribution networks (WDNs). A higher dose of chlorine is required in an overhead service reservoir to maintain minimum residual chlorine at the farthest end in WDNs. However, delivering high dosages of chlorine from storage tanks can pose public health issues, especially for the residents living near overhead service reservoirs due to the formation of trihalomethanes, haloacetic acids, and chlorophenols. In addition, a higher dosage will lead to increased chlorine consumption and will accelerate pipe corrosion. Booster chlorination (BC) stations with smaller dosages are a solution to this problem. However, identifying the optimal number, locations, and dosage of each BC station in a cost-effective manner is challenging. This study proposes a methodology for determining the optimal number, locations, and chlorine dosages of BC stations in WDNs using a mixed integer linear programming problem. The methodology is illustrated through a simplified WDN in Holeta town, Ethiopia. The results indicate that if one adds two BC stations beyond the three dosage stations at the source, it will lead to a 49% reduction in chlorine use and a 27% decrease in the life cycle cost. HIGHLIGHTS To propose a methodology for identifying the optimal number, locations, and chlorine dosage at various BC stations in a water distribution network (WDN).; Trade-offs between the chlorine mass dosage required and the life cycle cost for different numbers of BC stations are evaluated.; To illustrate the proposed methodology through a real-type WDN of Holeta town in Ethiopia to ensure safe drinking water for the residents.;

Precise value of scheduling decisions forms the cornerstone of water distribution network (WDN) scheduling optimization, which aims at conserving energy and enhancing network operational efficiency. This article proposes a computational methodology for evaluating the value chain of scheduling decisions in WDN. The scheduling process is modeled as a Markov decision process with immediate reward function, action and state space. Due to the periodicity of water supply and sequential nature of scheduling, the calculation quantifies cumulative value of scheduling decisions by incorporating state transition probability with expected value. The effectiveness and applicability of the proposed evaluation method are demonstrated using scheduling data from a real world WDN. The method provides rational values on scheduling period and strategies, offering practical feedback for scheduling decisions.

In the context of global efforts to address climate change, research into regional carbon neutrality strategies has become especially critical. For developing countries and regions, it is essential to scientifically and rationally assessing the paths for small-scale regional transformations under carbon neutrality imperatives to effectively implement low-carbon transition measures. This study utilizes Chongming District in Shanghai of China as a case to establish a framework for forecasting carbon emission and sink from a multi-dimensional natural-social perspective. This facilitates the simulation and optimization of pathways for carbon neutrality transformation. The results indicate: (1) From 2000 to 2020, the total regional carbon emission exhibited a rising trend, while the total carbon sink initially declined then increased, indicating potential enhancement zone with significant potential and space for carbon neutrality development. (2) Enhanced management of ecological spaces and land use planning result in notable increases in carbon sink. Strategic measures such as emission and consumption reductions, alongside energy transitions, effectively controlled carbon emission growth and facilitated comprehensive decarbonization. (3) By combining ecological priority with enhanced control and balanced development with enhanced control, the region can achieve carbon neutrality. This showcases the effective role of policy regulation in facilitating high-quality carbon–neutral transformations. (4)Effective ecosystem management along with robust reduction and transition strategies enable county-level carbon–neutral transformations, offering a model and methodological support for other developing regions facing the twin challenges of economic growth and environmental sustainability.

The persistence, bioaccumulation, and toxicity of perfluorinated and polyfluoroalkyl substances (PFASs), along with their concentrations in the environment and humans, have attracted global attention. However, so far, there have been seldom reports providing a systematical review in the entire field of PFASs research. Therefore, this study summarizes 14,112 relevant publications (2005–2022) and conducts bibliometric analysis using Vosviewer and CiteSpace. The findings offer insights into global PFASs research trends, assisting scientists in establishing their research directions. Unlike traditional literature reviews, this article presents a new method for data collection and analysis that achieves quantitative visualization of the information from the past 18 years in the field of PFASs. Results show a significant increase in global PFASs publications, with China leading in publication output and the US in international collaborations. Author Kurunthachalam Kanna has the highest publication records. Document co-citation clustering and key line analysis identifies four major research areas and landmarks, while betweenness centrality analysis reveals developmental processes. Citation burst analysis finds that PFASs toxicity and monitoring have been hot areas, suggesting the need for greater attention towards the types and levels of PFASs in various environmental media and the removal processes of PFASs responsible for pollution, which may emerge as future research hotspots.

Negligently partially closed in-line valves in pipes cause undesirable minor head losses that reduce the carrying capacity and increase operating costs attributable to energy consumption. However, few obtained results of in-line valves condition assessment has been offered in the literature. The paper makes further investigations on the interaction between the valve and the transient pressure wave, which provides experimental data support and reference opinions for the transient wave detection of in-line valve status with practical applications. The position of the in-line valve is evaluated by a simple equation and the propagation of transient pressure wave was analyzed. The relevant equations are derived and correlation analysis was performed. Based on the pressure increase value, the head loss coefficient or valve opening degree can be determined, and feasible suggestions for detecting the valve opening degree using transient waves have been made. Under the selected experimental conditions, the absolute error between the calculated valve opening degree and the actual opening degree is below 0.06 (1 for fully open valve opening and 0 for fully closed valve opening), proving that the valve opening assessment method is effective. This paper demonstrates the application of transient wave technology in real-time monitoring and assessment of valve positions. Through this technology, the valve positions in water distribution systems can be optimized effectively, thereby reducing resistance losses, meeting varying water demands, avoiding unnecessary energy waste, and enhancing the overall energy efficiency of the water supply system.

Facing the dual pressure of eutrophication control and global phosphorus scarcity, the efficient removal and recovery of phosphate from wastewater has attracted growing attention in recent years. Herein, an efficient nanocomposite (nCaO2-BFS) was successfully synthesized through a facile coprecipitation method by loading nano-calcium peroxide (nCaO2) onto blast furnace slags (BFS) and used for phosphate removal and recovery from wastewater. Based on the preliminary screening of as-prepared nCaO2-BFS sorbents regarding phosphate removal efficiency, the nCaO2-BFS nanocomposite prepared with a CaCl2-to-BFS mass ratio of 0.6:1, NH3·H2O amount of 20 mL, and H2O2 amount of 12 mL was selected for further characterization and phosphate elimination. Results showed that the developed nCaO2-BFS sorbent exhibits a superior adsorption capacity of 67.48 mg·g-1, a broadly applicable pH range from 4 to 10, and strong selectivity for phosphate in the presence of competing anions including Cl-, NO3-, SO42-, HCO3-, and CO32-. Mechanistically, surface precipitation and inner-sphere complexation via ligand exchange were identified as the primary sorption mechanism for nCaO2-BFS in capturing phosphate. The plant growth test confirmed that the phosphate-laden nCaO2-BFS sorbent could be used as a slow-release fertilizer to promote the growth of Brassica rapa L. Therefore, applying nCaO2-BFS appears to be a promising method for remediating excessive phosphate and recovering the non-renewable phosphorus resource.

Within the framework of global climate change, there is a recurring occurrence of floods and waterlogging disasters, which pose significant risks to human lives and overall safety. The phenomenon of urbanization has led to an increased vulnerability of cities to flood disasters. Evacuation serves as a viable strategy for adapting to climate change, managing intense precipitation events, and mitigating the impact of flood disasters. Hence, the meticulous choice of shelters has emerged as a crucial element in enhancing the effectiveness of evacuations. Nevertheless, the process of choosing shelters sometimes neglects to consider the potential for flooding and has not undergone thorough testing. Hence, the objective of this research is to systematically choose shelters within the central metropolitan region, incorporate flood risk considerations into the shelter site model, and assist cities in mitigating the consequences of floods resulting from climate change. To begin with, employ a two-dimensional shallow water model in order to replicate instances of intense precipitation and produce data on flood inundation. Subsequently, the simulation results are utilized to assess the flood risk using the entropy weight approach. This risk is then incorporated into the multi-objective optimization model to determine the optimal shelter placement. Ultimately, the ABM model was employed to create a simulation of crowd evacuation in urban areas, confirming the efficacy of shelter selection and thoroughly examining the influence of various shelters on the efficiency of community emergency evacuation. The study's findings indicate that a total of 26 shelters were chosen within the study area using a multi-objective methodology, ensuring the inclusion of all affected populations. The utilization of multi-objective models in the selection of shelter places has been shown to enhance evacuation efficiency, as confirmed by the ABM model. The simulation findings indicate a decline in the population's death rate from 1.94% to 0.98%, an increase in the evacuation rate from 97.4% to 98.4%, and a reduction in the number of casualties by 133 individuals.

The outbreak of algal blooms caused by cyanobacteria has led to a significant concern regarding water safety due to the release of microcystins. This study aimed to investigate the release and removal of microcystins (RR, LR) using coagulant polyaluminum chloride (PAC) with the assistance of nano-Fe3O4 particles. The findings indicate that the addition of PAC alone resulted in the rupture of Microcystis aeruginosa cells, leading to the release of microcystins into the water. PAC alone faced challenges in coagulating and removing the extracellular microcystins, especially at low dosages, but increasing the dosage of PAC could promote the release of intracellular microcystins. When combined with nano-Fe3O4, even a low concentration of PAC exhibited effective removal of microcystins in water. The presence of nano-Fe3O4 facilitated the hydrolysis of PAC, resulting in the production of Alc, which enhanced the coagulation performance of PAC. Furthermore, the addition of nano-Fe3O4 significantly improved the removal rate of microcystins by coagulant PAC under different pH conditions. Notably, at pH 5, the residual amount of microcystins was only about 7% compared to PAC alone. This study holds great significance in terms of achieving safer and more economical removal of microcystins from water.

The consumption of natural resources and waste production raises questions and concerns for the global scientific community and government decision-makers. This review article provides several literature references related to the concept of the circular economy and how the transition from a linear to a more circular system would prove to be a particularly sustainable practice in resource and waste management, ensuring the sustainable use and minimized consumption of resources, but also the reduced production, the reuse and the controlled disposal of waste as nutrients of a subsequent system. Also, bibliographic references give information about the actions and the Action Plan of the European Union in a sustainable policy, as well as the expected goals from this activity. This article review provides adequate liiterature references regarding the principles of the circular economy in the agri-food sector as well as the necessity of its implementation to address the existing challenges that the specific sector must face and the benefits that can arise from such a transition.

Soil erosion and sedimentation are the major threats to Ethiopia’s economy by impacting the productivity of agricultural land and shortening the life of dams. Ayigebire watershed was one of the most erosion-susceptible watersheds in Menz Gera district of Ethiopia. At the outlet, there was a soil dam (Godebe soil dam) which covered 12.7 ha. The dam was designed for irrigation purposes wishing to serve 378 households on 68 ha of land. However, the dam was facing a huge challenge of siltation due to the soil erosion brought from the upper reaches of the watershed. Therefore, the purpose of this study was to identify the erosion-affected area and to estimate the watershed's annual sediment yield delivered to the dam. The study used rainfall, DEM and satellite image data obtained from different sources. The result shows the annual soil loss of the watershed was 47 tons ha−1 yr−1. The regions along the drainage lines were identified as erosion hotspot areas and they contribute 76.6% of soil loss. The estimated annual sediment washed from the watershed and reached the Godebe soil dam was found to be 8710 m3 (60969 m3) since the time the dam became operational). From the finding, it could be concluded that the watershed was highly vulnerable to soil loss above the tolerable soil loss limit of the country i.e., 10 tons ha−1 yr−1. Therefore, it’s recommended the high erosion and sediment-producing areas along the waterlines and side banks of the dam get priority for management.

Abstract: Given the threat of fossil fuel depletion, it is essential to proactively strive for carbon neutrality and promote clean, low-carbon and efficient energy use. This study used ERA5 reanalysis data to assess wind energy resources in the Pacific Northwest region. By analyzing key indicators such as wind power density, effective wind speed occurrence, and energy level occurrence, climate statistics and Empirical Orthogonal Function analysis (EOF) were used to examine the spatial distribution and long-term trend of offshore wind energy resources in the Northwest Pacific. The results suggest that there are abundant wind energy resources in this region, which are beneficial for the development of offshore wind energy. The rich areas are the East China Sea, Taiwan islands and reefs in the South China Sea and east of Japan, with prevailing wind power density (500 ∼ 2500 W/m2) and effective wind speed occurrence (80–90%) and energy level occurrence (60% ∼ 90%). Offshore wind energy resources in the Pacific Northwest are more abundant in fall and winter than in summer. The time coefficient of the first mode shows that the offshore wind energy in the Northwest Pacific has no obvious change trend, and the wind energy resources are relatively stable.

Climate variability significantly affects the overall agricultural production and productivity over space and time. To quantify the effect of climate variability on natural systems on Earth in the future, the use of regional climate models (RCMs) as a tool is mandatory. Thus, the use of well-validated RCM provides efficient climate data; and predicts future climate variability over agroecological zones (AEZs). Eleven RCMs from CORDEX-Ethiopia were evaluated to simulate maximum temperature (Tmax), minimum temperature (Tmin) and rainfall variability over space and time, to validate their performance and to select the best-fit models. The temporal variability Tmax and rainfall was smaller with a CV of 10 %, indicating uniform distribution over stations. However, CV for Tmin over stations shows satisfactory distributions. Most of the evaluated RCMs have a better capability to capture the spatial variability of rainfall,Tmax, and Tmin in some stations. However, some of the RCMs can handle the spatial variability of Tmax while others are not. None of the RCMs can handle the spatial variability of Tmin in Debre Birhan, Majete, and Kewat AEZs. In general, most RCMs can capture the spatial and temporal variability of rainfall and temperature. It might be better to use the ensemble average of the output from these RCMs for precise estimation of data than specific RCMs. Therefore, this work could suggest the use of high-resolution RCMs for the projection of temperature and rainfall over different AEZs.

We perform an economic feasibility analysis for installing grid-connected solar arrays with batteries to power ten water supply, distribution, and treatment stations in Ciudad Juárez in tandem with the existing local grid. This article covers detailed results from the four stations that represent the topographical and geographical variability of the city and the variable electricity demand across sites. Using data from the city’s water utility and calculations from the HOMER and RETScreen models, we find contrasting results. The HOMER model finds that solar arrays with or without batteries are economically viable while RETScreen reaches the opposite conclusion. One key reason for this is the two models’ differing predictions on the amount of electricity the proposed solar arrays would supply. Further, having reliable battery storage is paramount to overcoming grid outages and the intermittent availability of solar power to ensure the success of solar projects. Global scientific consensus recognizes the need for more renewable energy. With a sunny-climate and its status as a manufacturing hub on the US-Mexico border, Ciudad Juárez has the potential to lead the way forward in promoting solar energy. The comparative results of the HOMER and RETScreen models provide a more complete understanding of the feasibility of solar power for Ciudad Juárez’s water infrastructure as well as vital insight into the factors that shape the success of solar projects.

A substantial environmental and societal problem is posed by pollutants found in aqueous solution. These pollutants generally consist of dangerous heavy metals and metalloids. In rural locations, hardness and chlorides are among the most dangerous problems of groundwater. Chlorides are regulated in the quality of drinking water because excessive quantities can cause disease. Due to its alkaline nature, both the gaseous and liquid forms of hardness can be irritating to the eyes, respiratory system, and epidermis. The acute biologic effects of hardness and chlorides in humans are dependent on dose and proportionate to their concentration. This includes the amount that is eaten by the body as well as the length of time that the body is exposed to the substance. The naturally occurring physiochemical mechanism known as biosorption is what permits particular biomass to passively concentrate and bind pollutants to its cellular structure. Biosorption can only occur in specific environments. This is a metabolically inert process that does not need any kind of energy, and the quantity of pollutants that a sorbent is able to remove is dependent on its kinetic equilibrium as well as the makeup of its cellular surface. When it came to the biosorption of heavy metals from water, each biosorbent had its own unique set of physical, chemical, and biological features. After the removal of heavy metals, the biosorption process may be made more cost-effective by renewing and reprocessing the biosorbent. This is done after the heavy metals have been removed. In the process of biosorption, many types of bioreactors are used in order to successfully remove the metal ions from huge volumes of water.

With accelerated urban sprawl, water scarcity and increased water stress have become global issues. Water of building industry and domestic water are two major contributors to total water consumption that cannot be ignored. This paper seeks to emphasize the effects of urban sprawl on water competition between building industry and residents. To achieve this objective, a framework for quantifying the water usage of the life cycle of the building was first constructed. Additionally, the degree of urban sprawl and water competition between domestic and building industry was computed. This study characterized the evolution path of urban sprawl and water competition using standard deviation ellipse. Spatial econometric models were used to determine the impact of urban sprawl on water competition. The results indicate that there is a high spatial correlation between urban sprawl and water competition. The center of gravity of China's urban sprawl is consistent with the north-to-south movement of water competition. As economic sprawl increases by 1%, water competition will rise by 0.440%. As the population expands by 1%, the water competition index shifts by 0.018%. Moreover, 0.017% more water was used for every 1% increase in land sprawl.

In response to escalating global energy demands and mounting environmental concerns, Microbial Fuel Cells have emerged as a groundbreaking technology, leveraging the unique abilities of microorganisms to harness bioenergy. This comprehensive review delves into the foundational principles governing MFCs, exploring mechanisms facilitating electron transfer and bioenergy generation while addressing factors influencing MFC performance. It further analyzes MFCs' multifaceted applications, from wastewater treatment to bioenergy recovery, and investigates their synergistic integration with other renewable energy systems. Despite these promising prospects, this review acknowledges the challenges of scalability, cost-effectiveness, and optimization, highlighting recent advancements aimed at enhancing efficiency, stability, and economic viability in MFC research. This review further offers a holistic perspective on the dynamic field of MFCs, assessing their potential to revolutionize bioenergy production while recognizing the hurdles to widespread adoption.