Search Results (1,618)

Desalination plays a critical role in addressing global water scarcity, yet brine disposal remains a significant environmental challenge. This study evaluates a minimal liquid discharge (MLD) membrane-based system integrating high-pressure reverse osmosis (HPRO) and membrane distillation (MD) for brine treatment, with a focus on the Eastern Mediterranean. A techno-economic assessment (TEA) was conducted to analyze the system’s feasibility, water recovery performance, energy consumption, and cost-effectiveness. The results indicate that the hybrid HPRO-MD system achieves a high water recovery rate of 78.65%, with 39.65 m³/day recovered from MD and 39 m³/day from HPRO. The specific energy consumption is 23.2 kWh/m³, with MD accounting for 89% of the demand. The system’s cost is USD 0.99/m³, generating daily revenues of USD 228 in Cyprus and USD 157 in Greece. Compared to conventional brine disposal methods, MLD proves more cost-effective, particularly when considering evaporation ponds. While MLD offers a sustainable alternative for brine management, challenges remain regarding energy consumption and the disposal of concentrated waste streams. Future research should focus on renewable energy integration, advanced membrane technologies, and resource recovery through brine mining. The findings highlight the HPRO-MD MLD system as a promising approach for sustainable desalination and circular water resource management. Full article

In recent years, China’s rapid economic growth and urbanization have heightened the conflict between economic development and resource sustainability, leading to severe urban water challenges, including scarcity and environmental degradation. This study proposes a quantitative model that integrates the “Human-Water-City” (HWC) feedback mechanisms to assess and measure urban comprehensive water resources and environmental carrying capacity (CWRECC), aimed at addressing urban water sustainability challenges. The CWRECC integrates water quantity and quality dimensions following the principles of the “Cannikin Law”—selecting the lower envelope between water resources and water environment carrying capacities, which emphasizes the importance of weaknesses in enhancing the overall system. The maximum sustainable population and Gross Domestic Product (GDP) under the CWRECC constraints can be obtained using this quantitative method. A case study was conducted in Wuhan City. The results show that Wuhan has abundant water resources. From 2013 to 2020, if only considering the water quantity aspect, the water resources carrying capacity could support a population ranging from 22.63 to 61.17 million and a GDP between 1946.6 and 7988.9 billion yuan, maintaining a sustainable state throughout the period. However, when considering both water quantity and quality, the CWRECC revealed an overloaded state in 2013, 2014, 2018, and 2019, primarily attributable to significant water environmental issues. In 2013, 2014, 2018, and 2019, the quantified CWRECC could sustain populations of 9.88 million, 10.01 million, 10.33 million, and 10.57 million people, and support a GDP of 849.5 billion, 976.5 billion, 1402.9 billion, and 1538.9 billion yuan, respectively. Both the population and GDP capacities fell short of the actual recorded values for those years. The findings demonstrate that Wuhan needs to make greater efforts in water environmental protection to sustain the harmonious development within the HWC. This empirical study highlights the model’s potential to provide a scientific foundation for urban water resources management and environmental protection strategies. Full article

Monitoring freshwater resources is essential for assessing the impacts of drought, water management and global warming. Spaceborne LiDAR altimeters allow researchers to obtain water height information, while water area and precipitation data can be obtained using different satellite systems. In our study, we examined 5 years (2018–2022) of data concerning the Euphrates–Tigris Basin (ETB), one of the most important freshwater resources of the Middle East, and the water bodies of both the ETB and the largest lake of Türkiye, Lake Van. A multi-sensor study aimed to detect and monitor water levels and water areas in the water scarcity basin. The ATL13 product of the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) was used to determine water levels, while the normalized difference water index was applied to the Sentinel-2 optical imaging satellite to monitor the water area. Variations in both water level and area may be related to the time series of precipitation data from the ECMWF Reanalysis v5 (ERA5) product. In addition, our results were compared with global HydroWeb water level data. Consequently, it was observed that the water levels in the region decreased by 5–6 m in many reservoirs after 2019. It is noteworthy that there was a decrease of approximately 14 m in the water level and 684 km² in the water area between July 2019 and July 2022 in Lake Therthar. Full article

Given the growing adverse effects of drought on water resources, agriculture, and various sectors, assessing and evaluating drought and producing high-quality drought maps despite the data scarcity to better understand its impacts and develop effective mitigation strategies is essential. Considering the existing gaps related to drought evaluation, especially in scarce data regions, this research aims to evaluate the efficiency of acceptable time period for drought studies (10–20 years), evaluate the performance of ERA5-LAND and IMERG-NASA precipitation data in estimating the Standardized Precipitation Index (SPI) using different statistical metrics and the innovative drought classification matrix (IDCM), and finally produce and compare high-quality and accurate drought characteristics maps resulted from in situ stations, ERA5-LAND, and IMERG-NASA. The Kocaeli province in Türkiye, which has limited data and is a scarce data region, has been selected as an application. The results ensure that an acceptable time period can be sufficient and provide reliable accuracy for assessing drought with RMSE ranging between 0.09 and 0.23 standard deviation and IDCM ranging between 85% and 97%. NASA IMERG data gave more accurate drought results than ERA5-LAND, and the Pearson correlation ranges between 0.57 and 0.89. Also, in situ data showed longer drought duration, while ERA5-LAND and NASA had higher intensity. This article enables policymakers and decision-makers to manage and plan water resources within the city boundary, ensuring sustainable agricultural, economic, and industrial activities and supporting effective climate change adaptation strategies. Full article

The Euphrates–Tigris Basin is experiencing significant environmental transformations due to climate change, Land Use and Land Cover Change (LULCC), and anthropogenic pressures. This study employs Earth Map, an open-access remote sensing platform, to comprehensively assess climate trends, vegetation dynamics, water resource variability, and land degradation across the basin. Key findings reveal a geographic shift toward aridity, with declining precipitation in high-altitude headwater regions and rising temperatures exacerbating water scarcity. While cropland expansion and localized improvements in land productivity were observed, large areas—particularly in hyperarid and steppe zones—show early signs of degradation, increasing the risk of dust source expansion. LULCC analysis highlights substantial wetland loss, irreversible urban growth, and agricultural encroachment into fragile ecosystems, with Iraq experiencing the most pronounced transformations. Climate projections under the SSP245 and SSP585 scenarios indicate intensified warming and aridity, threatening hydrological stability. This study underscores the urgent need for integrated water management, Land Degradation Neutrality (LDN), and climate-resilient policies to safeguard the basin’s ecological and socioeconomic resilience. Earth Map is a vital tool for monitoring environmental changes, offering rapid insights for policymakers and stakeholders in this data-scarce region. Future research should include higher-resolution datasets and localized socioeconomic data to improve adaptive strategies. Full article

Background: Examining medico-legal cases within hospitals aids in identifying care-related problems, facilitating necessary corrections and emphasizing successful preventive measures. The case of Meyer Children’s Hospital is particularly noteworthy as it offers insights into the evolution of litigation in regard to a tertiary pediatric hospital. Methods: The study sample comprised 158 malpractice claims received by Meyer Children’s Hospital from 1 January 2010 to 31 December 2023, which were managed by the Claims Management Committee (CMC) responsible for civil liability within the hospital. In this observational retrospective study, the following variables were analyzed: (1) The characteristics of the patients (age–sex) and the manner in which they interacted with the hospital, ultimately resulting in the compensation claim (method of access, area of specialty, outcomes based on the International Classification of Patient Safety (ICPS)). (2) Medico-legal factors: the details of the compensation claim, the significant issues noted in various cases, and the findings of the medico-legal inquiry conducted by the CMC. In cases of ADR (Alternative Dispute Resolution), we evaluated the nature of the procedure, the results, and the amount of compensation awarded. Results: We conducted a descriptive statistical analysis to delineate the trend of claims and identify specific deficiencies within structures or departments over time. Invasive procedures and surgical operations were identified as the leading causes of accidents, resulting in heightened mortality rates and serious injuries. The most common errors observed were diagnostic and therapeutic. Conclusions: The data that emerged highlighted a low rate of claims (11.28/year) and a low claim/service ratio (0.0002%), suggesting a high level of safety of patient care at the hospital. The acceptance rate (32%), the percentage of rejected cases (48/158~30% of total, or 48/99~49% of resolved claims), the average compensation (EUR 68,312), and the percentage of cases (92%) with judicial opinions consistent with those of the CMC indicate a tendency to pursue exploratory compensation requests and the effectiveness of CMC’s activity. Meanwhile, the predominant error types (surgical and diagnostic) are in accordance with national and international data. Finally, the scarcity of disputes concerning informed consent reflects the impressive effectiveness of the communication strategies utilized by the pediatricians at this center. Full article

Efficient irrigation management is essential for optimizing yield and quality in specialty crops like hot peppers (Capsicum chinense), particularly under controlled greenhouse environments. This study employed a novel sensor-based system integrating soil moisture and sap flux monitoring to evaluate water use dynamics in Capsicum chinense, a species for which such applications have not been widely reported. Three cultivars—Habanero, Helios, and Lantern—were grown under three volumetric soil moisture contents: low (15%), medium (18%), and high (21%). Water uptake was measured at leaf (transpiration, stomatal conductance) and plant levels (sap flux via heat balance sensors). Photosynthesis, fruit yield, and capsaicinoid concentrations were assessed. Compared to high irrigation, medium and low irrigation increased photosynthesis by 16.6% and 22.2%, respectively, whereas high irrigation favored greater sap flux and vegetative growth. Helios exhibited an approximately 8.5% higher sap flux as compared to Habanero and about 10% higher as compared to Lantern. Helios produced over 30% higher fruits than Habanero and Lantern under high irrigation. Habanero recorded the highest pungency, with a capsaicinoid level of 187,292 SHU—exceeding Lantern and Helios by 56% and 76%, respectively. Similarly, nordihydrocapsaicin and dihydrocapsaicin accumulation were more cultivar-dependent than irrigation-dependent. No significant interaction between cultivar and irrigation was observed, indicating genotype-driven water use strategies. Our study contributes to precision horticulture by integrating soil moisture and sap flux sensors to reveal cultivar-specific water use strategies in Capsicum chinense, thereby demonstrating the potential of an integrated sensor-based irrigation system for efficient irrigation management under increasing water scarcity in protected environments. As a preliminary greenhouse study aimed at maintaining consistent irrigation throughout the growing season across three volumetric soil moisture levels, these findings provide a foundation for subsequent validation and exploration under diverse soil moisture conditions including variations in stress duration, stress frequency, and stress application at different phenological stages. Full article

Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive maps of key soil health descriptors by integrating satellite-based indicators with a recently released geo-referenced soil dataset. A machine learning model was applied to estimate a suite of soil properties, including organic carbon, pH, texture fractions, macronutrients, and electrical conductivity. The resulting maps reflect spatial patterns consistent with previous studies focused on Cyprus and provide high resolution insights into degradation processes, such as organic carbon loss, and salinization risk. These outputs provide added value for identifying priority zones for soil conservation and evidence-based land management planning. While predictive uncertainty is greater in areas lacking ground reference data, particularly in the northeastern part of the island, the modeling framework demonstrates strong potential for a national-scale soil health assessment. The outcomes are directly relevant to ongoing soil policy developments, including the forthcoming Soil Monitoring Law, and provide spatial prediction models and indicator maps that support the assessment and mitigation of soil degradation. Full article

As global energy systems transition towards greater reliance on renewable energy sources, the integration of energy storage systems (ESSs) becomes increasingly critical to managing the intermittency and variability associated with renewable generation. This paper provides a comprehensive review of the application of evolutionary game theory (EGT) to optimize ESSs, emphasizing its role in enhancing decision-making processes, operation scheduling, and multi-agent coordination within dynamic, decentralized energy environments. A significant contribution of this paper is the incorporation of negotiation mechanisms and collaborative decision-making frameworks, which are essential for effective multi-agent coordination in complex systems. Unlike traditional game-theoretic models, EGT accounts for bounded rationality and strategic adaptation, offering a robust tool for modeling the interactions among stakeholders such as energy producers, consumers, and storage operators. The paper first addresses the key challenges in integrating ESS into modern power grids, particularly with high penetration of intermittent renewable energy. It then introduces the foundational principles of EGT and compares its advantages over classical game theory in capturing the evolving strategies of agents within these complex environments. A key innovation explored in this review is the hybridization of game-theoretic models, combining the stability of classical game theory with the adaptability of EGT, providing a comprehensive approach to resource allocation and coordination. Furthermore, this paper highlights the importance of deliberative democracy and process-based negotiation decision-making mechanisms in optimizing ESS operations, proposing a shift towards more inclusive, transparent, and consensus-driven decision-making. The review also examines several case studies where EGT has been successfully applied to optimize both local and large-scale ESSs, demonstrating its potential to enhance system efficiency, reduce operational costs, and improve reliability. Additionally, hybrid models incorporating evolutionary algorithms and particle swarm optimization have shown superior performance compared to traditional methods. The future directions for EGT in ESS optimization are discussed, emphasizing the integration of artificial intelligence, quantum computing, and blockchain technologies to address current challenges such as data scarcity, computational complexity, and scalability. These interdisciplinary innovations are expected to drive the development of more resilient, efficient, and flexible energy systems capable of supporting a decarbonized energy future. Full article

The outlook for biobased plastics in packaging applications is increasingly promising, driven by a combination of environmental advantages, technological innovation, and shifting market dynamics. Derived from renewable biological resources, these materials offer compelling benefits over conventional fossil-based plastics. They can substantially reduce greenhouse gas emissions, are often recyclable or biodegradable, and, in some cases, require less energy to produce. These characteristics position biobased plastics as a key solution to urgent environmental challenges, particularly those related to climate change and resource scarcity. Biobased plastics also demonstrate remarkable versatility. Their applications range from high-performance barrier layers in multilayer packaging to thermoformed containers, textile fibers, and lightweight plastic bags. Notably, all major fossil-based packaging applications can be substituted with biobased alternatives. This adaptability enhances their commercial viability across diverse sectors, including food and beverage, pharmaceutical, cosmetics, agriculture, textiles, and consumer goods. Several factors are accelerating growth in this sector. These include the increasing urgency of climate action, the innovation potential of biobased materials, and expanding government support through funding and regulatory initiatives. At the same time, consumer demand is shifting toward sustainable products, and companies are aligning their strategies with environmental, social, and governance (ESG) goals—further boosting market momentum. However, significant challenges remain. High production costs, limited economies of scale, and the capital-intensive nature of scaling biobased processes present economic hurdles. The absence of harmonized policies and standards across regions, along with underdeveloped end-of-life infrastructure, impedes effective waste management and recycling. Additionally, consumer confusion around the disposal of biobased plastics—particularly those labeled as biodegradable or compostable—can lead to contamination in recycling streams. Overcoming these barriers will require a coordinated, multifaceted approach. Key actions include investing in infrastructure, advancing technological innovation, supporting research and development, and establishing clear, consistent regulatory frameworks. Public procurement policies, eco-labeling schemes, and incentives for low-carbon products can also play a pivotal role in accelerating adoption. With the right support mechanisms in place, biobased plastics have the potential to become a cornerstone of a sustainable, circular economy. Full article

The 2021 WHO classification of brain tumours revolutionised the oncological field by emphasising the role of molecular, genetic and pathogenetic advances in classifying brain tumours. In this context, incidental gliomas have been increasingly identified due to the widespread performance of standard and advanced MRI sequences and represent a diagnostic and therapeutic challenge. The impactful decision to perform a surgical procedure deeply relies on the non-invasive identification of features or parameters that may correlate with brain tumour genetic profile and grading. Therefore, it is paramount to reach an early and proper diagnosis through neuroradiological techniques, such as MRI. Standard MRI sequences are the cornerstone of diagnosis, while consolidated and emerging roles have been awarded to advanced sequences such as Diffusion-Weighted Imaging/Apparent Diffusion Coefficient (DWI/ADC), Perfusion-Weighted Imaging (PWI), Magnetic Resonance Spectroscopy (MRS), Diffusion Tensor Imaging (DTI) and functional MRI (fMRI). The current novelty relies on the application of AI in brain neuro-oncology, mainly based on radiomics and radiogenomics models, which enhance standard and advanced MRI sequences in predicting glioma genetic status by identifying the mutation of multiple key biomarkers deeply impacting patients’ diagnosis, prognosis and treatment, such as IDH, EGFR, TERT, MGMT promoter, p53, H3-K27M, ATRX, Ki67 and 1p19. AI-driven models demonstrated high accuracy in glioma detection, grading, prognostication, and pre-surgical planning and appear to be a promising frontier in the neuroradiological field. On the other hand, standardisation challenges in image acquisition, segmentation and feature extraction variability, data scarcity and single-omics analysis, model reproducibility and generalizability, the black box nature and interpretability concerns, as well as ethical and privacy challenges remain key issues to address. Future directions, rooted in enhanced standardisation and multi-institutional validation, advancements in multi-omics integration, and explainable AI and federated learning, may effectively overcome these challenges and promote efficient AI-based models in glioma management. The aims of our multidisciplinary review are to: (1) extensively present the role of standard and advanced MRI sequences in the differential diagnosis of iLGGs as compared to HGGs (High-Grade Gliomas); (2) give an overview of the current and main applications of AI tools in the differential diagnosis of iLGGs as compared to HGGs (High-Grade Gliomas); (3) show the role of MRI, radiomics and radiogenomics in unravelling glioma genetic profiles. Standard and advanced MRI, radiomics and radiogenomics are key to unveiling the grading and genetic profile of gliomas and supporting the pre-operative planning, with significant impact on patients’ differential diagnosis, prognosis prediction and treatment strategies. Today, neuroradiologists are called to efficiently use AI tools for the in vivo, non-invasive, and comprehensive assessment of gliomas in the path towards patients’ personalised medicine. Full article

The water–energy–food (WEF) nexus provides a critical framework for addressing the interconnected challenges of resource scarcity and sustainability in the face of global population growth and climate variability. This study investigates the application of a WEF nexus approach within the operation and management of a hydroponic greenhouse unit in Central Greece, with the aim of enhancing the unit’s energy autonomy and resource sufficiency. Hydroponics, a soilless cultivation method, optimizes water and land use but relies heavily on energy inputs, necessitating integrated solutions. Through the case study approach, we analyze the unit’s resource dynamics per hectare of water (68 MWh equivalent from desalination), energy (125 MWh or 321 GJ/ha plus 74.5 GJ/ha for fertigation), and food production (~295 tons, which contains 50,250,000 kcal and corresponds to 210 GJ) and propose technical solutions: photovoltaic panels as greenhouse coverings and water rain harvesting regulated with a small reservoir. These innovations could reduce external energy dependency by 90–95% and water use by 25–35%. Energy efficiency is quantified using the energy ratio (ER) and net energy gain (NEG), while resilience is assessed via system reliability under resource variability. Conclusively, this study illustrates how a nexus-based approach can effectively upgrade systems into climate-resilient, resource-efficient models as the abundance or scarcity of one source affects the availability or limitation of the others. Overall, the approach presented in this study could also be used to safeguard the supply chains in megacities. Full article

Effective water resource management plays a crucial role in achieving sustainability in agriculture, hydrology, and environmental protection, particularly under growing water scarcity and climate-related challenges. Soil moisture (θ), matric potential (h), and hydraulic conductivity (K) are critical parameters influencing water availability for crops and regulating hydrological, environmental, and ecological processes. To address the need for accurate, real-time soil monitoring in both laboratory and open-field conditions, we proposed an innovative IoT-based monitoring system called SHYPROM (Soil HYdraulic PROperties Meter), designed for the simultaneous estimation of parameters θ, h, and K at different soil depths. The system integrates capacitive soil moisture and matric potential sensors with wireless communication modules and a cloud-based data processing platform, providing continuous, high-resolution measurements. SHYPROM is intended for use in both environmental and agricultural contexts, where it can support precision irrigation management, optimize water resource allocation, and contribute to hydrological and environmental monitoring. This study presents recent technological upgrades to the proposed monitoring system. To improve the accuracy and robustness of θ estimates, the capacitive module was enhanced with an integrated oscillator circuit operating at 60 MHz, an upgrade from the previous version, which operated at 600 kHz. The new system was tested (i.e., calibrated and validated) through a series of laboratory experiments on soils with varying textures, demonstrating its improved ability to capture dynamic soil moisture changes with greater accuracy compared to the earlier SHYPROM version. During calibration and validation tests, soil water content data were collected across a θ range from 0 to 0.40 cm³/cm³. These measurements were compared to reference θ values obtained using the thermo-gravimetric method. The results show that the proposed monitoring system can be used to obtain predictions of θ values with acceptable accuracy (R² values range between 0.91 and 0.96). To further validate the performance of the upgraded SHYPROM system, evaporation experiments were also conducted, and the θ(h) and K(θ) relationships were determined among soils. Retention and conductivity data were fitted using the van Genuchten and van Genuchten–Mualem models, respectively, confirming that the device accurately captures the temporal evolution of soil water status (R² values range from 0.97 to 0.99). Full article

The energy self-sufficiency of wastewater treatment plants has become an essential aspect of sustainable water and energy resource management. On the other hand, due to the expansion of urban conglomerations and agricultural activities, as well as more frequent and erratic meteorological phenomena (e.g., droughts), the majority of EU nations are confronted with water scarcity and the deterioration of water quality. As a consequence, EU member states pledged to implement “tertiary treatment” in all municipal wastewater treatment facilities by the end of 2040. This publication presents an analysis of the efficiency of an energy-efficient gravity cloth disk filter used for treating municipal wastewater in a treatment plant located in a tourist resort in Poland, operating under variable hydraulic loading conditions. Gravity cloth disk filters appear to be the least energy-consuming. The energy consumption of disk filters was 13 Wh/m³ in 2024. The filter ensures the leveling of disturbances in the operation of earlier treatment stages, particularly in terms of retaining total suspended solids (TSSs). The achieved efficiency of TSS removal was 45%. The TSS value in the outflow from the filter did not exceed the limit value from the permit (35 mg/L). When operated correctly, additional filtration and disinfection may become essential components of a wastewater treatment plant, enabling the achievement of wastewater quality that supports water recovery for technological and agricultural purposes, particularly in small, non-industrial areas. They should also consume less energy than other advanced technologies used in the third and fourth stages of wastewater treatment. Full article

Industrial tree plantations (ITPs) are increasingly recognized as a sustainable response to deforestation and the decline in native wood resources in the Philippines. This study presents LUNTIAN (Labor, UNiversity, Timber Investment, and Agent-based Nexus), an agent-based model that simulates an experimental ITP operation within a mountain forest managed by University of the Philippines Los Baños. The model integrates biophysical processes—such as tree growth, hydrology, and stand dynamics—with socio-economic components such as investment decision making based on risk preferences, employment allocation influenced by local labor availability, and informal harvesting behavior driven by job scarcity. These are complemented by institutional enforcement mechanisms such as forest patrolling, reflecting the complex interplay between financial incentives and rule compliance. To assess the model’s validity, its outputs were compared to those of the 3PG forest growth model, with results demonstrating alignment in growth trends and spatial distributions, thereby supporting LUNTIAN’s potential to represent key ecological dynamics. Sensitivity analysis identified investor earnings share and community member count as significant factors influencing net earnings and management costs. Parameter calibration using the Non-dominated Sorting Genetic Algorithm yielded an optimal configuration that ensured profitability for resource managers, investors, and community-hired laborers while minimizing unauthorized independent harvesting. Notably, even with continuous harvesting during a 17-year rotation, the final tree population increased by 55%. These findings illustrate the potential of LUNTIAN to support the exploration of sustainable ITP management strategies in the Philippines by offering a robust framework for analyzing complex social–ecological interactions. Full article