Search Results (294)

A mass abatement scalable system through managed aquifer recharge (MAR-MASS) improves mass extraction from groundwater with a variable-density flow. This method is superior to conventional injection systems because it promotes uniform mass displacement, reduces density gradients, and increases mass extraction efficiency over time. Simulations of various scenarios involving hydrogeologic variables, including hydraulic conductivity, vertical anisotropy, specific yield, mechanical dispersion, molecular diffusion, and mass concentration in aquifers, have identified critical variables and parameters influencing mass transport interactions to optimize the system. MAR-MASS is adaptable across hydrogeologic conditions in aquifers that are 25–75 m thick, comprising unconsolidated materials with hydraulic conductivities between 5 and 100 m/d. It is effective in scenarios near coastal areas or in aquifers with variable-density flows within the continent, with mass concentrations of salts or solutes ranging from 3.5 to 35 kg/m³. This system employs a modular approach that offers scalable and adaptable solutions for mass extraction at specific locations. The integration of programming tools, such as Python 3.13.2, along with technological strategies utilizing parallelization techniques and high-performance computing, has facilitated the development and validation of MAR-MASS in mass extraction with remarkable efficiency. This study confirmed the utility of these tools for performing calculations, analyzing information, and managing databases in hydrogeologic models. Combining these technologies is critical for achieving precise and efficient results that would not be achievable without them, emphasizing the importance of an advanced technological approach in high-level hydrogeologic research. By enhancing groundwater quality within a comparatively short time frame, expanding freshwater availability, and supporting sustainable aquifer recharge practices, MAR-MASS is essential for improving water resource management. Full article

The interconnections among water, energy, and food (WEF) systems are growing increasingly complex, making it essential to understand their evolutionary mechanisms and coordination barriers to enhance regional resilience and sustainability. In this study, we investigated the WEF system in Northeast China by constructing a comprehensive indicator system encompassing resource endowment and utilization efficiency. The coupling coordination degree (CCD) of the WEF system was quantitatively assessed from 2001 to 2022. An obstacle degree model was employed to identify key constraints, while grey relational analysis was used to evaluate the driving influence of individual indicators. Furthermore, a co-evolution model based on logistic growth and competition–cooperation dynamics was developed to simulate system interactions. The results reveal the following: (1) the regional WEF-CCD increased from 0.627 in 2001 to 0.769 in 2022, reaching the intermediate coordination level, with the CCDs of the food, water, and energy subsystems rising from 0.39 to 0.62, 0.38 to 0.60, and 0.40 to 0.55, respectively, highlighting that the food subsystem had the most stable and significant improvement; (2) Jilin Province attained the highest WEF-CCD, 0.850, in 2022, while that for Heilongjiang remained the lowest, at 0.715, indicating substantial interprovincial disparities; (3) key indicators, such as food self-sufficiency rate, electricity generation, and ecological water use, functioned as both core constraints and major drivers of system performance; (4) co-evolution modeling revealed that the food subsystem exhibited the fastest growth, followed by water and energy (${\alpha }_3$ >${ \alpha }_1$ > ${ \alpha }_2$ > 0), with mutual promotion between water and energy subsystems and inhibitory effects from the food subsystem, ultimately converging toward a stable equilibrium state; and (5) interprovincial co-evolution modeling indicated that Jilin leads in WEF system development, followed by Liaoning and Heilongjiang, with predominantly cooperative interactions among provinces driving convergence toward a stable and coordinated equilibrium despite structural asymmetries. This study proposes a transferable, multi-method analytical framework for evaluating WEF coordination, offering practical insights into bottlenecks, key drivers, and co-evolutionary dynamics for sustainable resource governance. Full article

According to Victor Ernest Shelford’s ‘Law of Tolerance,’ organisms within ecosystems thrive optimally when environmental conditions are favorable. Applying this principle to ecosystems and agro-ecosystems facing water scarcity or environmental challenges can significantly enhance their productivity. In these ecosystems, phytocenosis adjusts its conditions by utilizing water with varying salinity levels. Moreover, establishing optimal drinking water conditions for human populations within an ecosystem can help mitigate future negative succession processes. The purpose of this study is to evaluate the quality of two distinct water sources in the Amudarya district of the Republic of Karakalpakstan, Uzbekistan: collector-drainage water and groundwater at depths of 10 to 25 m. This research is highly relevant in the context of climate change, as improper management of water salinity, particularly in collector-drainage water, may exacerbate soil salinization and degrade drinking water quality. The primary methodology of this study is as follows: The Food and Agriculture Organization of the United Nations (FAO) standard for collector-drainage water is applied, and the water quality index is assessed using the CCME WQI model. The Canadian Council of Ministers of the Environment (CCME) model is adapted to assess groundwater quality using Uzbekistan’s national drinking water quality standards. The results of two years of collected data, i.e., 2021 and 2023, show that the water quality index of collector-drainage water indicates that it has limited potential for use as secondary water for the irrigation of sensitive crops and has been classified as ‘Poor’. As a result, salinity increased by 8.33% by 2023. In contrast, groundwater quality was rated as ‘Fair’ in 2021, showing a slight deterioration by 2023. Moreover, a comparative analysis of CCME WQI values for collector-drainage and groundwater in the region, in conjunction with findings from Ethiopia, India, Iraq, and Turkey, indicates a consistent decline in water quality, primarily due to agriculture and various other anthropogenic pollution sources, underscoring the critical need for sustainable water resource management. This study highlights the need to use organic fertilizers in agriculture to protect drinking water quality, improve crop yields, and promote soil health, while reducing reliance on chemical inputs. Furthermore, adopting WQI models under changing climatic conditions can improve agricultural productivity, enhance groundwater quality, and provide better environmental monitoring systems. Full article

The Altay oasis, located at the heart of the transnational ecological conservation zone shared by China, Kazakhstan, Russia, and Mongolia, is a region with tremendous potential for water resource utilization. However, with the continued expansion of agriculture, its ecological vulnerability has become increasingly pronounced. Within this fragile balance lies a critical opportunity: efficient water resource management could pave the way for sustainable development across the entire arid oasis regions. This study uses a decision tree model based on a feature threshold to map the spatial distribution of major crops in the Altay Prefecture oasis, assess their water requirements, and identify the coupling relationships between agricultural water and land resources. Furthermore, it proposed optimization planting structure strategies under three scenarios: water-saving irrigation, cash crop orientation, and forage crop orientation. In 2023, the total planting area of major crops in Altay Prefecture was 3368 km², including spring wheat, spring maize, sunflower, and alfalfa, which consumed 2.68 × 10⁹ m³ of water. Although this area accounted for only 2.85% of the land, it consumed 26.23% of regional water resources, with agricultural water use comprising as much as 82.5% of total consumption, highlighting inefficient agricultural water use as a critical barrier to sustainable agricultural development. Micro-irrigation technologies demonstrate significant water-saving potential. The adoption of such technologies could reduce water consumption by 14.5%, thereby significantly enhancing agricultural water-use efficiency. Cropping structure optimization analysis indicates that sunflower-based planting patterns offer notable water-saving benefits. Increasing the area of sunflower cultivation by one unit can unlock a water-saving potential of 25.91%. Forage crop combinations excluding soybean can increase livestock production by 30.2% under the same level of water consumption, demonstrating their superior effectiveness for livestock system expansion. This study provides valuable insights for achieving sustainable agricultural development in arid regions under different development scenarios. Full article

Under the context of global climate change, sea-level rise and frequent storm surge events pose significant challenges to coastal areas. Protecting coastlines from erosion, mitigating socio-economic losses, and maintaining ecosystem balance are critical for the sustainable development of coastal zones. The concept of “living shorelines” based on Nature-based Solutions (NbS) employs near-natural ecological restoration and protection measures. In low-energy coastal segments, natural materials are prioritized, while high-energy segments are supplemented with artificial structures. This approach not only enhances disaster resilience but also preserves coastal ecosystem stability and ecological functionality. This study constructs a coastal vitality evaluation system for Fujian Province, China, using the entropy weight method, integrating three dimensions: protective safety, ecological resilience, and economic vitality. Data from 2010 and 2020 were analyzed to assess the spatiotemporal evolution of coastal vitality. Results indicate that coastal vitality initially exhibited a spatial pattern of “low in the north, high in the center, and low in the south,” with vitality values ranging from 0.20 to 0.67 (higher values indicate stronger vitality). Over the past decade, ecological restoration projects have significantly improved coastal vitality, particularly in central and southern regions, where high-vitality segments increased markedly. Key factors influencing coastal vitality include water quality, cyclone intensity, biological shoreline length, and wetland area. NbS-aligned coastal management strategies and soft revetment practices have generated substantial ecological and economic benefits. To further enhance coastal vitality, region-specific approaches are recommended, emphasizing rational resource utilization, optimization of ecological and economic values, and the establishment of a sustainable evaluation framework. This study provides scientific insights for improving coastal protection capacity, ecological resilience, and economic potential. Full article

The planting area of the maize–soybean strip intercropping system has been increasing annually in the Hexi Corridor oasis irrigation area of China. However, long-term irrational water resource utilization and the excessive mono-application of fertilizers have led to significantly low water and nitrogen use efficiency in this cropping system. To explore the sustainable production model of high yield and high water–nitrogen productivity in maize–soybean strip intercropping, we established three irrigation levels (low: 60%, medium: 80%, and sufficient: 100% of reference crop evapotranspiration) and three nitrogen application levels (low: maize 230 kg ha⁻¹, soybean 29 kg ha⁻¹; medium: maize 340 kg ha⁻¹, soybean 57 kg ha⁻¹; and high: maize 450 kg ha⁻¹, soybean 85 kg ha⁻¹) for maize and soybean, respectively. Three irrigation levels without nitrogen application served as controls. The effects of different water–nitrogen combinations on multiple indicators of the maize–soybean strip intercropping system, including yield, water–nitrogen productivity, and quality, were analyzed. The results showed that the irrigation amount and nitrogen application rate significantly affected the kernel quality of maize. Specifically, the medium nitrogen and sufficient water (N2W3) combination achieved optimal performance in crude fat, starch, and bulk density. However, excessive irrigation and nitrogen application led to a reduction in the content of lysine and crude protein in maize, as well as crude fat and crude starch in soybean. Appropriate irrigation and nitrogen application significantly increased the yield in the maize–soybean strip intercropping system, in which the N2W3 treatment had the highest yield, with maize and soybean yields reaching 14007.02 and 2025.39 kg ha⁻¹, respectively, which increased by 2.52% to 138.85% and 5.37% to 191.44% compared with the other treatments. Taking into account the growing environment of the oasis agricultural area in the Hexi Corridor and the effects of different water and nitrogen supplies on the yield, water–nitrogen productivity, and kernel quality of maize and soybeans in the strip intercropping system, the highest target yield can be achieved when the irrigation quotas for maize and soybeans are set at 100% ET0 (reference crop evapotranspiration), with nitrogen application rates of 354.78~422.51 kg ha⁻¹ and 60.27~71.81 kg ha⁻¹, respectively. This provides guidance for enhancing yield and quality in maize–soybean strip intercropping in the oasis agricultural area of the Hexi Corridor, achieving the dual objectives of high yield and superior quality. Full article

Desalination is becoming crucial to meet the increasing global demand for potable water. Despite its benefits, desalination produces reject brine, a highly concentrated saline byproduct, which poses substantial environmental risks if not managed properly. It contains high levels of salts and other potentially harmful compounds, which, when discharged into oceans or land, can disrupt habitats, degrade soil quality, and harm biodiversity, creating serious environmental challenges. In response to these challenges, this study investigated various uses for reject brine, aiming to reduce its environmental footprint and explore its potential applications. This review paper synthesizes findings from previous studies on the disposal, management, and applications of reject brine in fields such as concrete production, road construction, and ground stabilization. In addition, this review highlights the potential cost savings and resource efficiency resulting from the utilization of reject brine, as well as the mitigation of environmental impacts associated with traditional disposal methods. This paper also provides a comprehensive overview of existing technologies and approaches used to utilize reject brine in various industries, including construction. This review contributes to the growing body of knowledge on environmentally friendly solutions for reject brine, emphasizing its potential role in supporting sustainable development goals through resource reutilization and waste minimization. The study also highlights current research gaps that are still unaddressed, hindering the complete realization of the full potential of reject brine as a sustainable resource. Full article

Groundwater serves as a vital resource for sustainable water supply, particularly in semi-arid regions where surface water availability is limited. This study explores groundwater potential zones in the East Desert, Qift–Qena, Egypt, using a multidisciplinary approach that integrates remote sensing (RS), geographic information systems (GIS), geostatistics, and field validation with water wells to develop a comprehensive groundwater potential mapping framework. Sentinel-2 imagery, ALOS PALSAR DEM, and SMAP datasets were utilized to derive critical thematic layers, including land use/land cover, vegetation indices, soil moisture, drainage density, slope, and elevation. The results of the groundwater potentiality map of the study area from RS reveal four distinct zones: low, moderate, high, and very high. The analysis indicates a notable spatial variability in groundwater potential, with “high” (34.1%) and “low” (33.8%) potential zones dominating the landscape, while “very high” potential areas (4.8%) are relatively scarce. The limited extent of “very high” potential zones, predominantly concentrated along the Nile River valley, underscores the river’s critical role as the primary source of groundwater recharge. Moderate potential zones include places where infiltration is possible but limited, such as gently sloping terrain or regions with slightly broken rock structures, and they account for 27.3%. These layers were combined with geostatistical analysis of data from 310 groundwater wells, which provided information on static water level (SWL) and total dissolved solids (TDS). GIS was employed to assign weights to the thematic layers based on their influence on groundwater recharge and facilitated the spatial integration and visualization of the results. Geostatistical interpolation methods ensured the reliable mapping of subsurface parameters. The assessment utilizing pre-existing well data revealed a significant concordance between the delineated potential zones and the actual availability of groundwater resources. The findings of this study could significantly improve groundwater management in semi-arid/arid zones, offering a strategic response to water scarcity challenges. Full article

The performance of photovoltaic systems is highly dependent on environmental conditions, with soiling due to dust accumulation often being referred to as a predominant energy degradation factor, especially in dry and semi-arid environments. This paper introduces an AI-based robotic cleaning system that can independently forecast and schedule cleaning sessions from real-time sensor and environmental data. Methods: The system integrates sources of data like embedded sensors, weather stations, and DustIQ data to create an integrated dataset for predictive modeling. Machine learning models were employed to forecast soiling loss based on significant atmospheric parameters such as relative humidity, air pressure, ambient temperature, and wind speed. Dimensionality reduction through the principal component analysis and correlation-based feature selection enhanced the model performance as well as the interpretability. A comparative study of four conventional machine learning models, including logistic regression, k-nearest neighbors, decision tree, and support vector machine, was conducted to determine the most appropriate approach to classifying cleaning needs. Results: Performance, based on accuracy, precision, recall, and F1-score, demonstrated that logistic regression and SVM provided optimal classification performance with accuracy levels over 92%, and F1-scores over 0.90, demonstrating outstanding balance between recall and precision. The KNN and decision tree models, while slightly poorer in terms of accuracy (around 85–88%), had computational efficiency benefits, making them suitable for utilization in resource-constrained applications. Conclusions: The proposed system employs a dry-cleaning mechanism that requires no water, making it highly suitable for arid regions. It reduces unnecessary cleaning operations by approximately 30%, leading to decreased mechanical wear and lower maintenance costs. Additionally, by minimizing delays in necessary cleaning, the system can improve annual energy yield by 3–5% under high-soiling conditions. Overall, the intelligent cleaning schedule minimizes manual intervention, enhances sustainability, reduces operating costs, and improves system performance in challenging environments. Full article

The cosmetic industry in the Ecuadorian Amazon region faces the challenge of competitively integrating locally sourced plant-based raw materials into efficient and sustainable production processes. This study proposes the design of a pilot plant for the production of a cosmetic emulsion (CE), using oils extracted from Morete (Mauritia flexuosa) and Ungurahua (Oenocarpus bataua), with a focus on process intensification to reduce both capital investment and resource consumption. Process design methodologies and computational simulation (SuperPro Designer V10) were applied, along with Systematic Layout Planning (SLP) principles to optimize spatial configuration. The intensified scheme enabled the integration of extraction lines, reducing the number of major equipment units from 12 to 9 and lowering the investment from USD 1,016,000 to USD 719,000. Energy and environmental indicators showed consumption levels of 5.86 kWh and 48.4 kg of water per kg of cream, which are lower than those reported for other natural cosmetics plants. The intensified design achieved a Net Present Value (NPV) of USD 577,000 and a payback period of 3.93 years. Furthermore, solid by-products were valorized through circular economy principles. This approach offers a feasible, viable, and sustainable solution for the utilization of these Amazonian oils in the cosmetic industry. Full article

Arsenic contamination in water poses a significant global health risk, necessitating efficient and sustainable remediation strategies. Arsenic contamination affects groundwater in at least 106 countries, potentially exposing over 200 million people to elevated levels, primarily through contaminated drinking water. Among the most affected regions, Bangladesh remains a critical case study, where widespread reliance on shallow tubewells has resulted in one of the largest mass poisonings in history. Bio-based nanomaterials have emerged as promising solutions due to their eco-friendly nature, cost-effectiveness, and high adsorption capabilities. These nanomaterials offer a sustainable approach to arsenic remediation, utilizing materials like biochar, modified biopolymers, and bio-based aerogels, which can effectively adsorb arsenic and other pollutants. The use of environmentally friendly nanostructures provides a potential option for improving the efficiency and sustainability of arsenic remediation from groundwater. This review explores the mechanisms underlying arsenic remediation using such nanomaterials, including adsorption, filtration/membrane technology, photocatalysis, redox reactions, complexation, ion exchange, and coagulation–flocculation. Despite their potential, challenges such as scalability, stability, and regeneration hinder widespread application. We discuss recent advancements in material design, surface modifications, and hybrid systems that enhance performance. Finally, future perspectives are highlighted, including the integration of these bio-derived systems with smart sensing technologies, sustainable water-treatment frameworks, smart design, and life-cycle integration strategies, particularly for use in resource-constrained regions like Bangladesh and other globally impacted areas. Full article

In the face of increasingly complex urban challenges, a critical question arises: can urban ecosystems maintain resilience, vitality, and sustainability when confronted with external threats and pressures? Taking Kunming—a plateau-mountainous city in China—as a case study, this research constructs an urban ecosystem resilience (UER) assessment model based on the DPSIR (Driving forces, Pressures, States, Impacts, and Responses) framework. A total of 25 indicators were selected via questionnaire surveys, covering five dimensions: driving forces such as natural population growth, annual GDP growth, urbanization level, urban population density, and resident consumption price growth; pressures including per capita farmland, per capita urban construction land, land reclamation and cultivation rate, proportion of natural disaster-stricken areas, and unit GDP energy consumption; states measured by Evenness Index (EI), Shannon Diversity Index (SHDI), Aggregation Index (AI), Interspersion and Juxtaposition Index (IJI), Landscape Shape Index (LSI), and Normalized Vegetation Index (NDVI); impacts involving per capita GDP, economic density, per capita disposable income growth, per capita green space area, and per capita water resources; and responses including proportion of natural reserve areas, proportion of environmental protection investment to GDP, overall utilization of industrial solid waste, and afforestation area. Based on remote sensing and other data, indicator values were calculated for 2006, 2011, and 2016. The entire-array polygon indicator method was used to visualize indicator interactions and derive composite resilience index values, all of which remained below 0.25—indicating a persistent low-resilience state, marked by sustained economic growth, frequent natural disasters, and declining ecological self-recovery capacity. Forecasting results suggest that, under current development trajectories, Kunming’s UER will remain low over the next decade. This study is the first to integrate the DPSIR framework, entire-array polygon indicator method, and Grey System Forecasting Model into the evaluation and prediction of urban ecosystem resilience in plateau-mountainous cities. The findings highlight the ecosystem’s inherent capacities for self-organization, adaptation, learning, and innovation and reveal its nested, multi-scalar resilience structure. The DPSIR-based framework not only reflects the complex human–nature interactions in urban systems but also identifies key drivers and enables the prediction of future resilience patterns—providing valuable insights for sustainable urban development. Full article

As urbanization progresses at an accelerating pace, the depletion of natural resources and environmental degradation are becoming increasingly severe. Constructing ecological security patterns (ESPs) has become a crucial strategy for mitigating environmental stress and promoting sustainable social development. Currently, the methods for constructing ESPs remain under exploration. Particularly, in the identification of ecological sources, insufficient emphasis has been placed on trade-offs among ecosystem services (ESs). This study focuses on Liaoning Province, situated in China’s northeast revitalization area—a region with a developed heavy industry and abundant ecological resources. The InVEST model was employed to assess ESs, and the ordered weighted average (OWA) method was utilized to identify ecological sources. By integrating both natural and social factors, the ecological resistance surface was constructed, and circuit theory was applied to determine ecological corridors, ultimately leading to the development of an ESP. The results show that (1) between 2010, 2015, and 2020, water yield continued to increase, habitat quality continuously declined, soil conservation tended to decrease and then gradually increase, and carbon storage tended to increase and then decrease. The four ESs show similar spatial features, characterized by elevated levels in the eastern and western areas and a comparatively reduced level in the central region; (2) a total of 179 ecological sources were identified, covering 26,235.34 km². The overall distribution showed a concentration in the east, with a fragmented and dispersed pattern in the southwest. The identification of 435 ecological corridors, with an overall length totaling 8794.59 km, resulted in a network-like distribution pattern. Additionally, 65 ecological pinch points and 67 barrier points were identified; and (3) a “four zones, three corridors, and two belts” pattern of ecological protection and restoration has been proposed. The findings offer valuable insights for Liaoning Province and other rapidly developing regions facing escalating environmental pressures. Full article

It is essential to emphasize the significant impacts of climate change, which are evident in the form of severe and prolonged droughts, hurricanes, snowstorms, and other climatic disturbances. These challenges are particularly pronounced in urban environments and among human populations. The situation is further aggravated by the increasing utilization of available open spaces for residential and industrial development, leading to heightened energy consumption, elevated pollution levels, and increased carbon emissions, all of which negatively affect public health. The primary objective of this review article is to provide a comprehensive evaluation of current research, with a particular focus on the innovative use of residual biomass from urban vegetation for biochar production in the United States. This research entails an exhaustive review of existing literature to assess the implementation of a carbon-negative wood biomass biochar system as a strategic approach to sustainable urban management. By transforming urban wood waste—including tree trimmings, construction debris, and storm-damaged timber—into biochar through pyrolysis, a thermochemical process that sequesters carbon while generating renewable energy, we can leverage this valuable resource. The resulting biochar offers a range of co-benefits: it enhances soil health, improves water retention, reduces stormwater runoff, and lowers greenhouse gas emissions when applied in urban green spaces, agriculture, and land restoration projects. This review highlights the advantages and potential of converting urban wood waste into biochar while exploring how municipalities can strengthen their green ecosystems. Furthermore, it aims to provide a thorough understanding of how the utilization of woody biomass biochar can contribute to mitigating urban carbon emissions across the United States. Full article

This paper focuses on the social effect assessment of the ecological governance of Poyang Lake wetland in Jiangxi Province. By distributing 1098 valid questionnaires to the surrounding residents and collecting them, this paper deeply explores the feedback on residents’ satisfaction and recognition regarding the effectiveness of wetland governance measures. Through the comprehensive use of the Order Logit model and descriptive statistical methods such as the mean and standard deviation, this paper deeply discusses the impact of the ecological management measures of Poyang Lake wetland on residents’ life quality, environmental protection awareness, and community well-being. The study found that the wetland ecological management project was widely praised, and the overall satisfaction of residents was as high as 87.5%, reflecting a significant social effect. Further analysis revealed that satisfaction was affected by multiple factors, including age, education, quality of life (including increased leisure and recreational space and enhanced regional identity), and improvement in environmental quality (including increased bird species diversity, improved water and air quality, and improved infrastructure). Residents’ cognition of wetland function is multi-dimensional and profound, but they still need to strengthen standard science education in deep-level ecological functions such as species protection. Based on the research conclusion, three policy suggestions are proposed: first, the government should strengthen ecological education and enhance the public awareness of environmental protection; second, the government should pay attention to the win–win of ecology and people’s livelihoods and promote the harmonious coexistence of wetland protection and community development; and third, the government should improve the relevant infrastructure, strengthen environmental protection facilities, scientific research monitoring and legal construction, and lay a solid foundation for the sustainable protection and utilization of wetland resources. Full article