Search Results (13,115)

Grid-Scale Battery Energy Storage Systems (GS-BESS) play a crucial role in modern power grids, addressing challenges related to integrating renewable energy sources (RESs), load balancing, peak shaving, voltage support, load shifting, frequency regulation, emergency response, and enhancing system stability. However, harnessing their full potential and lifetime requires intelligent operational strategies that balance technological performance, economic viability, and environmental sustainability. This systematic review examines how artificial intelligence (AI)-based intelligent optimization enhances GS-BESS performance, focusing on its techno-economic, environmental impacts, and policy and regulatory implications. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we review the evolution of GS-BESS, analyze its advancements, and assess state-of-the-art applications and emerging AI techniques for GS-BESS optimization. AI techniques, including machine learning (ML), predictive modeling, optimization algorithms, deep learning (DL), and reinforcement learning (RL), are examined for their ability to improve operational efficiency and control precision in GS-BESSs. Furthermore, the review discusses the benefits of advanced dispatch strategies, including economic efficiency, emissions reduction, and improved grid resilience. Despite significant progress, challenges persist in data availability, model generalization, high computational requirements, scalability, and regulatory gaps. We conclude by identifying emerging opportunities to guide the next generation of intelligent energy storage systems. This work serves as a foundational resource for researchers, engineers, and policymakers seeking to advance the deployment of AI-enhanced GS-BESS for sustainable, resilient power systems. By analyzing the latest developments in AI applications and BESS technologies, this review provides a comprehensive perspective on their synergistic potential to drive sustainability, cost-effectiveness, and energy systems reliability. Full article

Sustainable groundwater management is critical in semi-arid coastal regions, where municipal landfills pose a severe threat to aquifer integrity and long-term water security. However, there is still a lack of seasonally resolved hydrogeochemical monitoring around newly established landfills, particularly in rapidly urbanizing Mediterranean settings. This study assesses the hydrogeochemical impact of the newly operational Tangier Landfill and Recovery Center on local groundwater resources to inform sustainable remediation strategies. A combined approach was applied to samples collected in dry and wet seasons, using Piper and Stiff diagrams to trace facies evolution together with a dual-index assessment based on the Canadian (CCME-WQI) and Weighted Arithmetic (WAWQI) Water Quality Indices. Results show that upgradient waters remain of Good–Excellent quality and are dominated by Ca–HCO₃ facies, whereas downgradient wells display extreme mineralization, with EC up to 15,480 µS/cm and Cl⁻ and SO₄²⁻ exceeding 1834 and 2114 mg/L, respectively. At hotspot sites P4 and P8, As reaches 0.065 mg/L and Cd 0.006 mg/L, far above the WHO drinking-water guidelines. While the CCME-WQI captures the general salinity-driven degradation pattern, the WAWQI pinpoints these acute toxicity zones as Very poor–Unsuitable. The study demonstrates that rainfall intensifies toxicity through a seasonal “Piston Effect” that mobilizes stored contaminants rather than diluting them, underscoring the need for seasonally adaptive monitoring to ensure the environmental sustainability of landfill-adjacent aquifers. Full article

Increasing global water scarcity has intensified the adoption of water reuse as a sustainable strategy, particularly in regions affected by drought and pressure on natural resources. This paper presents a systematic review of the application of Life Cycle Assessment (LCA) in water reuse projects, focusing on research trends, methodological approaches, and opportunities for improvement. A systematic search was conducted in Web of Science, ScienceDirect, and Google Scholar for studies published from 2020 onwards using combinations of the keywords “life cycle assessment”, “LCA”, “water reuse”, “water recycling”, and “wastewater recycling”. Twelve studies were selected from 57 records identified, based on predefined eligibility criteria requiring quantitative LCA of water reuse systems. The results reveal a predominance of European research, reflecting regulatory advances and strong academic engagement in this field. The most frequently assessed impact categories were global warming, eutrophication, human toxicity and ecotoxicity, highlighting the environmental relevance of reuse systems. Energy consumption and water transport were identified as critical hotspots, especially in scenarios involving long distances and fossil-based energy sources. Nevertheless, most studies demonstrate that water reuse is environmentally viable, particularly when renewable energy and optimized logistics are applied. The review also emphasizes the need to better integrate economic and social dimensions and to adapt LCA methodologies to local conditions. Overall, the findings confirm LCA as a robust decision-support tool for sustainable planning and management of water reuse systems. Full article

This article examines the failure of the two most recent temporary housing programs implemented in Spain following two major disasters: the 2011 Lorca earthquake and the 2021 La Palma volcanic eruption. Despite differing hazard typologies, both cases resulted in incomplete and ultimately unsuccessful housing programs, with only 13 of the 60 planned units built in Lorca and 121 of the 200 planned units delivered in La Palma. Using a qualitative comparative case study approach, the research analyzes governance decisions, housing design, and implementation processes to assess their impact on the sustainability of post-disaster temporary housing. The analysis adopts the five dimensions of sustainability—environmental, economic, social, cultural, and institutional—as an integrated analytical framework for evaluating public management performance in post-disaster temporary housing. The findings show that early decision-making, shaped by political urgency, technical misjudgments, and the absence of adaptive governance, led to severe delays, cost overruns, inadequate and energy-inefficient construction, and the formation of marginalized settlements. This study concludes that the lack of regulatory frameworks, legal instruments, and operational protocols for temporary housing in Spain was a determining factor in both failures, generating vulnerability, prolonging recovery processes, and undermining sustainability across all five dimensions. By drawing lessons from these cases, this article contributes to debates on resilient and sustainable post-disaster recovery and highlights the urgent need for integrated regulatory frameworks for temporary housing in Spain. Full article

Renewable energy investment evaluation continues to rely predominantly on techno-economic and environmental criteria, while equity-related considerations remain weakly embedded within formal decision-support frameworks. Although recent research increasingly acknowledges social impacts, spatial constraints, policy uncertainty, and financing structures, these dimensions are rarely integrated in a systematic and operational manner into investment appraisal. This paper addresses this gap by advancing an equity-oriented conceptual framework for renewable energy investment evaluation. Using an integrative literature review combined with thematic analysis, the study synthesises insights from techno-economic assessment, multi-criteria decision-making, energy justice scholarship, and equity-focused modelling studies. The analysis demonstrates that existing evaluation approaches inadequately capture distributional impacts, accessibility constraints, differentiated vulnerability, and equity-adjusted risk. In response, the proposed framework systematises these equity dimensions and embeds them directly into the core logic of investment evaluation alongside conventional criteria. By consolidating fragmented research insights into a coherent evaluative structure, the study contributes to the literature by clarifying how equity can be operationalised within renewable energy investment decision-making. The framework provides a foundation for future empirical applications and supports more socially responsive and analytically robust investment evaluation. Full article

AI technologies are increasingly applied to optimize operations in both port and urban logistics systems, yet integration across the full maritime city chain remains limited. The objective of this study is to assess, using a simulation-based experiment, the impact of an AI-orchestrated control policy on the performance of port–city logistics relative to a baseline scheduler. The study proposes an AI-orchestrated approach that connects autonomous ships, smart ports, central warehouses, and multimodal urban networks via a shared cloud control layer. This approach is designed to enable real-time, cross-domain coordination using federated sensing and adaptive control policies. To evaluate its impact, a simulation-based experiment was conducted comparing a traditional scheduler with an AI-orchestrated policy across 20 paired runs under identical conditions. The orchestrator dynamically coordinated container dispatching, vehicle assignment, and gate operations based on capacity-aware logic. Results show that the AI policy substantially reduced the total completion time, lowered truck idle time and estimated emissions, and improved system throughput and predictability without modifying physical resources. These findings support the expectation that integrated, data-driven decision-making can significantly enhance logistics performance and sustainability in port–city contexts. The study provides a replicable pathway from conceptual architecture to quantifiable evidence and lays the groundwork for future extensions involving learning controllers, richer environmental modeling, and real-world deployment in digitally connected logistics corridors. Full article

Melamine, a nitrogen-rich industrial chemical, has raised increasing concern as an emerging environmental contaminant with potential reproductive toxicity. While its nephrotoxic effects are well established, the direct impact of melamine on human sperm remains poorly defined. In this study, we investigated the in vitro effects of melamine on human sperm, under both capacitating and non-capacitating conditions. Functional analyses revealed that the exposure to 0.8 mM melamine, the highest non-cytotoxic concentration in vitro, significantly compromised sperm motility and disrupted key capacitation processes, including tyrosine phosphorylation patterns, cholesterol efflux, and the acrosome reaction. Molecular assessments demonstrated melamine-induced mitochondrial dysfunction, characterized by COX4I1 downregulation, reduced mitochondrial membrane potential, and altered reactive oxygen species production. In parallel, gene expression analyses revealed the activation of apoptotic pathways, with the upregulation of BAX and downregulation of BCL2, changes that were more pronounced during capacitation. Furthermore, melamine exposure significantly increased sperm DNA fragmentation and denaturation, indicating genotoxic stress. Collectively, these findings demonstrate that even low, non-cytotoxic concentrations of melamine compromise sperm function by disrupting capacitation, mitochondrial activity, and genomic integrity. This study identifies capacitation as a critical window of vulnerability and underscores the need to consider melamine as a potential environmental risk factor for male reproductive health. Full article

This study examines the environmental implications of energy-intensive cryptocurrency mining activities within the broader sustainability debate surrounding blockchain technologies. Focusing specifically on Bitcoin’s proof-of-work–based mining process, the analysis investigates the long-run relationship between greenhouse gas emissions, network-specific technical variables, and climate policy uncertainty using advanced cointegration and asymmetric causality techniques. The findings reveal a stable long-run association between mining-related activity and emissions, alongside pronounced asymmetries whereby positive shocks amplify environmental pressures more strongly than negative shocks mitigate them. Importantly, these results pertain to the mining process itself rather than to blockchain technology as a whole. While blockchain infrastructures may support sustainable applications in areas such as green finance, transparency, and energy management, the evidence presented here highlights that energy-intensive mining remains a significant environmental concern. Accordingly, the study underscores the need for active regulatory frameworks—such as carbon pricing and the polluter-pays principle—to reconcile the environmental costs of crypto mining with the broader sustainability potential of blockchain-based innovations Full article

Tillage and crop rotation alter soil environments, thereby influencing both crop yields and methane-cycling microbiomes, yet their combined effects on microbial diversity, assembly, and interaction networks remain unclear. Using a two-factor field experiment, we assessed the impacts of raised seedbed vs. flat cultivation and rice–oilseed rape vs. rice–faba bean rotations on crop productivity and the ecology of methanogen (mcrA) and methanotroph (pmoA) communities. Raised seedbed cultivation significantly increased yields: rice yields were 7.6–9.6% higher in 2020 and 4.7–5.8% higher in 2021 than under flat cultivation (p < 0.05). Faba bean and oilseed rape yields were also improved. Flat rice–bean plots developed more reduced conditions and higher organic matter, with a higher NCM goodness-of-fit for methanogens (R² = 0.466), indicating patterns more consistent with neutral (stochastic) assembly, whereas the lower fit for methanotrophs (R² = 0.269) suggests weaker neutrality and stronger environmental filtering, accompanied by reduced richness and network complexity. In contrast, raised seedbed rice–oilseed rape plots improved redox potential and nutrient availability, sustaining both mcrA and pmoA diversity and fostering synergistic interactions, thereby enhancing community stability and indicating a potential for methane-cycle regulation. Overall, raised seedbed cultivation combined with legume rotation offers yield benefits and ecological advantages, providing a sustainable pathway for paddy management with potentially lower greenhouse gas risks. Full article

This paper introduces a mathematical model to assess the polluting impact of the decarbonization options for medium-sized High-Speed Crafts in the EU, and their consequences in terms of Market-Based Measure costs and Goal-Based Measure compliance under expected regulatory scenarios. This model is applied to a particular European High-Speed Craft operating in the Canary Islands. Considering slow steaming along with High Speed Craft’s retrofitting with alternative technologies for its electricity supply, we conclude that green H₂ fuel Cells provide the greatest environmental advantage by comparison with slow steaming alone, achieving a 6.96% improvement in emissions and savings under European Market-Based Measures of 39.76% by 2033. The expected regulative progression involves a 5.90% improvement in the Market-Based Measure costs’ convergence with the actual pollution impact of High-Speed Crafts. The findings warn about the pressing need to review the implementation of On-Shore Power Supply emissions into the Fuel EU fines, and about a concerning pull effect for the most polluting European High-Speed Crafts are moved towards the outermost regions of the EU due to their permanent exceptions from the application of the European Market-Based Measures. Full article

Nanoplastics (NPs) pose significant risks due to their small size and ability to penetrate biological tissues. However, the molecular pathways and cellular mechanisms affected by NP exposure in marine teleosts remain poorly understood, especially in tropical reef fishes. This study examined the impact of short-term (7 days) waterborne exposure of 100 nm-carboxyl-modified polystyrene NPs on the false clownfish (Amphiprion ocellaris) exposed at two daily concentrations: low (20 µg/L, environmentally relevant) and high (2000 µg/L). A multidisciplinary approach, including biochemical and transcriptomic analyses, was conducted to assess toxic effects. Biochemical assays revealed limited changes in antioxidant defenses (CAT, GR, GST, TOSC). However, the Integrated Biomarker Response index (IBRv2i) suggested a compromised physiological condition, supported by transcriptomic data. Transcriptomic profiling revealed 409 significantly differentially expressed genes (DEGs) in the high-concentration and 354 DEGs in the low-concentration groups, with 120 shared DEGs mostly upregulated and indicative of a core molecular response. Collectively, the transcriptional profile of the low-concentration group resembled an early-warning, energy-reallocation strategy aimed at preserving essential sensory functions while minimizing expendable functions. The high-concentration group amplified the shared stress signature and recruited an additional 289 unique genes, resulting in pronounced enrichment of Gene Ontology terms related to “muscle contraction”, “oxygen transport”, “hydrogen-peroxide catabolism”, and “extracellular-matrix”. This study demonstrates that PS-NP exposure can alter gene expression and physiology in juvenile reef fish, even at environmentally relevant concentrations. Molecular responses varied with concentrations highlighting the role of exposure level in influencing biological systems and potential long-term impacts of NP pollution in marine environments. Full article

The global energy landscape is transitioning towards cleaner solutions, with hydrogen emerging as a key energy source. To unlock hydrogen’s potential, it is crucial to prioritize the development of a more efficient, cost-effective, and environmentally friendly production process. Enhancing the efficiency and scalability of these technologies will not only reduce their environmental impact but also accelerate the adoption of hydrogen as a viable alternative energy solution, fostering a cleaner and more sustainable future. This paper presents a study on simulating a heat recovery system in an alkaline electrolyser consisting of 30 cells, which integrates a plate heat exchanger to preheat the water entering the system, and assessing how it affects efficiency. The study uses a thermal model, employing the concept of lumped thermal capacitance, to analyze the impact of the heat recovery system utilization on the overall performance of the electrolyser. MATLAB/Simulink was used to simulate and provide a detailed visualization of how recovery systems affect the electrolyser’s efficiency. The results of the simulations confirmed that incorporating a heat recovery system significantly improves the efficiency of alkaline electrolysers up to 8%. The study provides a promising outlook for the future of hydrogen production, emphasizing the potential of waste heat recovery systems to make green hydrogen production more viable and sustainable. Full article

The purpose of this study is to determine the optimal location for siting an onshore wind farm on the island of Skyros, thereby maximizing performance and minimizing the project’s environmental impacts. Seven evaluation criteria are defined across various sectors, including environmental and economic sectors, and six criteria weighting methods are applied in combination with four multicriteria decision-making (MCDM) ranking methods for suitable areas, resulting in twenty-four ranking models. The alternatives considered in the analysis were defined through the application of constraints imposed by the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD RES), complemented by exclusion criteria documented in the international literature, as well as a minimum area requirement ensuring the feasibility of installing at least four wind turbines within the study area. The correlations between their results are then assessed using the Spearman coefficient. Geographic information systems (GISs) are utilized as a mapping tool. Through the application of the methodology, it emerges that area A9, located in the central to northern part of Skyros, is consistently assessed as the most suitable site for the installation of a wind farm based on nine models combining criteria weighting and MCDM methods, which should be prioritized as an option for early-stage wind farm siting planning. The results demonstrate an absolute correlation among the subjective weighting methods, whereas the objective methods do not appear to be significantly correlated with each other or with the subjective methods. The ranking methods with the highest correlation are PROMETHEE II and ELECTRE III, while those with the lowest are TOPSIS and VIKOR. Additionally, the hierarchy shows consistency across results using weights from AHP, BWM, ROC, and SIMOS. After applying multiple methods to investigate correlations and mitigate their disadvantages, it is concluded that when experts in the field are involved, it is preferable to incorporate subjective multicriteria analysis methods into decision-making problems. Finally, it is recommended to use more than one MCDM method in order to reach sound decisions. Full article

Gas-insulated transmission lines (GILs) are increasingly deployed in dense urban power networks, where complex construction activities may introduce external mechanical impacts and pose risks to pipeline structural integrity. However, existing GIL monitoring approaches mainly emphasize electrical and gas-state parameters, while lightweight solutions capable of rapidly detecting and localizing impact-induced structural anomalies remain limited. To address this gap, this paper proposes an intelligent end-edge-cloud monitoring system for impact anomaly detection in GIL pipelines. Numerical simulations are first conducted to analyze the dynamic response characteristics of the pipeline under impacts of varying magnitudes, orientations, and locations, revealing the relationship between impact scenarios and vibration mode evolution. An end-tier multi-parameter intelligent sensor is then developed, integrating triaxial acceleration and angular velocity measurement with embedded lightweight computing. Laboratory impact experiments are performed to acquire sensor data, which are used to train and validate a multi-class extreme gradient boosting (XGBoost) model deployed at the edge tier for accurate impact-location identification. Results show that, even with a single sensor positioned at the pipeline midpoint, fusing acceleration and angular velocity features enables reliable discrimination of impact regions. Finally, a lightweight cloud platform is implemented for visualizing structural responses and environmental parameters with downsampled edge-side data. The proposed system achieves rapid sensor-level anomaly detection, precise edge-level localization, and unified cloud-level monitoring, offering a low-cost and easily deployable solution for GIL structural health assessment. Full article

Life-cycle assessment is crucial for evaluating materials’ environmental impact and guiding the development of low-carbon and sustainable buildings. However, conventional LCA methods often overlook critical impacts during the operation and maintenance stage. To address this gap, this study proposes an improved framework using four composite indicators to enable systematic evaluation of six wall materials across China’s five climate zones. Using a university teaching building in the Hot Summer and Cold Winter Zone as a case study, this study quantitatively analyzed the economic viability and carbon reduction potential of each material. Results indicate that lower thermal conductivity does not necessarily imply superior economic and carbon reduction performance. Factors including the material carbon emission factor, cost, and thermal properties, must be comprehensively considered. Buffering materials also exhibit climate dependency—WPM and BWPM (moisture-buffering plastering mortars) perform better in hot–humid zones than temperate zones. All five buffer materials reduce operational energy consumption; WPM and BWPM stand out with 15.7% and 16.7% life-cycle cost savings and 17.3% and 18.0% carbon emission reductions, respectively. This study addresses the limitations of traditional LCC/LCA and provides theoretical and practical support for scientific material selection and low-carbon building design. Full article