Search Results (524)

With the promotion of national fitness, the requirements for regulating indoor environments during non-competition periods are low and relatively flexible under the trend of composite sports buildings. To maximize the use of natural ventilation and lighting for energy savings, passive optimization design based on building ontology has emerged as an effective strategy. This paper focuses on the spatial prototype of large- and medium-sized gymnasiums, optimizing key geometric design parameters and envelope structure parameters that influence energy consumption. This optimization employs a combination of orthogonal experiments and performance simulations. This study identifies the degree to which each factor affects energy consumption in the competition hall and determines the optimal low-energy consumption gymnasium prototype. The results reveal that the skylight area ratio is the most significant factor impacting the energy consumption of large- and medium-sized gymnasiums. The optimized gymnasium prototype reduced energy consumption by 5.3%~50.9% compared to all experimental combinations. This study provides valuable references and insights for architects during the initial stages of designing sports buildings to achieve low energy consumption. Full article

This comprehensive review maps the fast-evolving landscape in which artificial intelligence (AI) and deep-learning (DL) techniques converge with the Internet of Things (IoT) to manage energy, comfort, and sustainability across smart environments. A PRISMA-guided search of four databases retrieved 1358 records; after applying inclusion criteria, 143 peer-reviewed studies published between January 2019 and April 2025 were analyzed. This review shows that AI-driven controllers—especially deep-reinforcement-learning agents—deliver median energy savings of 18–35% for HVAC and other major loads, consistently outperforming rule-based and model-predictive baselines. The evidence further reveals a rapid diversification of methods: graph-neural-network models now capture spatial interdependencies in dense sensor grids, federated-learning pilots address data-privacy constraints, and early integrations of large language models hint at natural-language analytics and control interfaces for heterogeneous IoT devices. Yet large-scale deployment remains hindered by fragmented and proprietary datasets, unresolved privacy and cybersecurity risks associated with continuous IoT telemetry, the growing carbon and compute footprints of ever-larger models, and poor interoperability among legacy equipment and modern edge nodes. The authors of researches therefore converges on several priorities: open, high-fidelity benchmarks that marry multivariate IoT sensor data with standardized metadata and occupant feedback; energy-aware, edge-optimized architectures that lower latency and power draw; privacy-centric learning frameworks that satisfy tightening regulations; hybrid physics-informed and explainable models that shorten commissioning time; and digital-twin platforms enriched by language-model reasoning to translate raw telemetry into actionable insights for facility managers and end users. Addressing these gaps will be pivotal to transforming isolated pilots into ubiquitous, trustworthy, and human-centered IoT ecosystems capable of delivering measurable gains in efficiency, resilience, and occupant wellbeing at scale. Full article

As an emerging energy-saving approach, bio-inspired drag reduction technology has become a key research direction for reducing energy consumption and greenhouse gas emissions. This study introduces the latest research progress on bio-inspired microstructured surfaces in the field of underwater drag reduction, focusing on analyzing the drag reduction mechanism, preparation process, and application effect of the three major technological paths; namely, bio-inspired non-smooth surfaces, bio-inspired superhydrophobic surfaces, and bio-inspired modified coatings. Bio-inspired non-smooth surfaces can significantly reduce the wall shear stress by regulating the flow characteristics of the turbulent boundary layer through microstructure design. Bio-inspired superhydrophobic surfaces form stable gas–liquid interfaces through the construction of micro-nanostructures and reduce frictional resistance by utilizing the slip boundary effect. Bio-inspired modified coatings, on the other hand, realize the synergistic function of drag reduction and antifouling through targeted chemical modification of materials and design of micro-nanostructures. Although these technologies have made significant progress in drag reduction performance, their engineering applications still face bottlenecks such as manufacturing process complexity, gas layer stability, and durability. Future research should focus on the analysis of drag reduction mechanisms and optimization of material properties under multi-physical field coupling conditions, the development of efficient and low-cost manufacturing processes, and the enhancement of surface stability and adaptability through dynamic self-healing coatings and smart response materials. It is hoped that the latest research status of bio-inspired drag reduction technology reviewed in this study provides a theoretical basis and technical reference for the sustainable development and energy-saving design of ships and underwater vehicles. Full article

The energy sector uses artificial intelligence (AI) as a crucial instrument to achieve environmental sustainability targets by improving resource efficiency and decreasing emissions while minimizing waste production. This paper establishes an industry-specific executive playbook that guides energy sector leaders by implementing AI technologies for sustainability management with approaches suitable for industrial needs. The playbook provides an industry-specific framework along with strategies and AI-based solutions to help organizations overcome their sustainability challenges. Predictive analytics combined with smart grid management implemented through AI applications produced 15% less energy waste and reduced carbon emissions by 20% according to industry pilot project data. AI has proven its transformative capabilities by optimizing energy consumption while detecting inefficiencies to create both operational improvements and cost savings. The real-time monitoring capabilities of AI systems help companies meet strict environmental regulations and international climate goals by optimizing resource use and waste reduction, supporting circular economy practices for sustainable operations and enduring profitability. Leaders can establish impactful technology-based sustainability initiatives through the playbook which addresses the energy sector requirements for corporate goals and regulatory standards. Full article

Against the backdrop of the profound restructuring in global climate governance, China’s energy management system is undergoing a comprehensive transition from dual energy consumption control to dual carbon emissions control. This policy shift fundamentally alters the underlying logic of energy-focused regulation and inevitably impacts the economy–energy–environment (3E) system. This study innovatively constructs a “Triangular Trinity” theoretical framework integrating internal, intermediate, and external triangular couplings, as well as providing a granular analysis of their transmission relationships and feedback mechanisms. Using Guangdong Province as a case study, this study takes the dual control emissions policy within the external triangle as an entry point to research the restructuring logic of dual carbon emissions control for the coupling coordination mechanisms of the 3E system. The key findings are as follows: (1) Policy efficacy evolution: During 2005–2016, dual energy consumption control significantly improved energy conservation and emissions reduction, elevating Guangdong’s 3E coupling coordination. Post 2017, however, its singular focus on total energy consumption revealed limitations, causing a decline in 3E coordination. Dual carbon emissions control demonstrably enhances 3E systemic synergy. (2) Decoupling dynamics: Dual carbon emissions control accelerates economic–carbon emission decoupling, while slowing economic–energy consumption decoupling. This created an elasticity space of 5.092 million tons of standard coal equivalent (sce) and reduced carbon emissions by 26.43 million tons, enabling high-quality economic development. (3) Mechanism reconstruction: By leveraging external triangular elements (energy-saving technologies and market mechanisms) to act on the energy subsystem, dual carbon emissions control leads to optimal solutions to the “Energy Trilemma”. This drives the systematic restructuring of the sustainability triangle, achieving high-order 3E coupling coordination. The Triangular Trinity framework constructed by us in the paper is an innovative attempt in relation to the theory of energy transition, providing a referenceable methodology for resolving the contradictions of the 3E system. The research results can provide theoretical support and practical reference for the low-carbon energy transition of provinces and cities with similar energy structures. Full article

This study evaluates and compares centralized and distributed reactive power compensation strategies using Static Var Compensators (SVCs) to enhance the performance of a high-voltage transmission system in the Caribbean region of Colombia. The methodology comprises four stages: system characterization, assessment of the uncompensated condition under peak demand, definition of four SVC-based scenarios, and steady-state analysis through power flow simulations using DIgSILENT PowerFactory. SVCs were modeled as Thyristor-Controlled Devices (“SVC Type 1”) operating as PV nodes for voltage regulation. The evaluated scenarios include centralized SVCs at the Slack node, node N4, and node N20, as well as a distributed scheme across load nodes N51 to N55. Node selection was guided by power flow analysis, identifying voltage drops below 0.9 pu and overloads above 125%. Technically, the distributed strategy outperformed the centralized alternatives, reducing active power losses by 37.5%, reactive power exchange by 46.1%, and improving node voltages from 0.71 pu to values above 0.92 pu while requiring only 437 MVAr of compensation compared to 600 MVAr in centralized cases. Economically, the distributed configuration achieved the highest annual energy savings (36 GWh), the greatest financial return (USD 5.94 M/year), and the shortest payback period (7.4 years), highlighting its cost-effectiveness. This study’s novelty lies in its system-level comparison of SVC deployment strategies under real operating constraints. The results demonstrate that distributed compensation not only improves technical performance but also provides a financially viable solution for enhancing grid reliability in infrastructure-limited transmission systems. Full article

With the increasingly stringent regulation of ship carbon emissions by the International Maritime Organization (IMO), improving ship energy efficiency has become a key research direction in the current shipping industry. This paper proposes and evaluates a comprehensive energy-saving solution that integrates a wind-assisted propulsion system (WAPS) and an organic Rankine cycle (ORC) waste heat power generation system. By establishing an energy efficiency simulation model of a typical ocean-going cargo ship, the appropriate optimal system configuration parameters and working fluids are determined based on minimizing the total fuel consumption, and the impact of these two energy-saving technologies on fuel consumption is systematically analyzed. The simulation results show that the simultaneous use of these two energy-saving technologies can achieve the highest energy efficiency, with the maximum fuel savings of approximately 21%. This study provides a theoretical basis and engineering reference for the design of ship energy-saving systems. Full article

The maritime sector is under pressure to increase ship energy efficiency and reduce greenhouse gas (GHG) emissions as a part of global decarbonization goals. Various innovative technologies are being adopted in recent years, raising concerns not only about technological feasibility but also about the economic viability of such technologies in the context of sustainable maritime practices. This study evaluates the operational performance, potential to increase energy efficiency, and economic feasibility of wind-assisted propulsion technologies such as rotor sails across different vessel types and operational profiles. As a contribution to cleaner and more efficient shipping, energy savings produced by rotor thrust were analyzed in relation to vessel dimensions and rotor configuration. The results derived from publicly available industry data including shipowner reports, manufacturer case studies, and classification society publications on 25 confirmed rotor sail installations between 2010 and 2025 indicate that savings typically range between 4% and 15%, with isolated cases reporting up to 25%. A simulation model was developed to assess payback time based on varying fuel consumption, investment cost, CO₂ pricing, and operational parameters. Monte Carlo analysis confirmed that under typical assumptions rotor sail investments can reach payback in three to six years (as the ship is also liable for CO₂ payments). These findings offer practical guidance for shipowners and operators evaluating wind-assisted propulsion under current and emerging environmental regulations and contribute to advancing sustainability in maritime transport. The research contributes to bridging the gap between simulation-based and real-world performance evaluations of rotor sail technologies. Full article

As global energy consumption continues to rise, it is essential to adopt measures that regulate electricity use while still meeting the demands of modern society. These efforts align with the United Nations Sustainable Development Goals and are supported by various organizations. This study applies a methodology that combines the implementation of a Level 2 Energy Audit with the evaluation of the Electricity Consumption Index (ECI) at the Department of English of the Multidisciplinary Academic Unit of the Altiplano Region, Universidad Autónoma de San Luis Potosí. The study identifies strategies to reduce electricity consumption related to lighting systems and equipment operation throughout the department. Additionally, it assesses the percentage of users who promote and practice energy-saving habits. Key recommendations include transitioning the lighting system to LED technology, expected to reduce electricity consumption by 15, and implementing power factor correction measures, projected to yield an additional 6.17% in energy and cost savings. Together, these strategies could result in an estimated annual electricity savings of 21.17%, making them attractive to institutional decision-makers. Furthermore, by comparing the department’s ECI with a reference index established for educational institutions in temperate climate regions of Mexico, the study determines whether the proposed strategies should be implemented immediately or planned for the medium to long term. This decision-making framework represents the main contribution of the case study. Full article

Broadband near-infrared (NIR) reflective films are widely used in architecture and the automotive and aerospace industries for energy saving and thermal regulation. For large-area and flexible applications, it is essential to develop cost-effective, solution-processable, and long-term-stable NIR-reflective films. Here, we present a polymer-stabilized chiral liquid crystal (CLC) film that achieves broadband NIR reflection by stacking opposite-handed CLC layers with pitch gradients. We experimentally established optimal formulations of materials for both right-handed and left-handed CLCs. The resulting film exhibits high-degree broadband reflection (~95%) in the 1000–1800 nm wavelength range, while maintaining visible transmittance (~80%) in the 450–850 nm range. The concept proposed here will be widely applicable for scalable and practical NIR-filtering applications in smart glasses, sensors, and optoelectronic devices. Full article

This study presents a comprehensive assessment of energy efficiency and conservation strategies in institutional buildings, using the Riyadh Reformatory Building (RRB) in Saudi Arabia as a case study. The analysis focuses on meeting the operational and safety requirements of the facility while aligning with the regulatory standards of the Saudi Arabian Standards Organization (SASO) and the Saudi Building Code (SBC Part 401), particularly in relation to electrical installations and the Energy Efficiency Ratio (EER) labeling system. Through simulation and evaluation, the study demonstrates that replacing traditional lighting with LED systems results in a 74% reduction in energy consumption. The application of programmable temperature regulators further reduces annual cooling energy use by 5.1%, with associated cost savings reaching 6.2%. Additionally, the research highlights the significant influence of window properties, thermal insulation, and water heater controls on energy performance. Notably, adopting high-EER air conditioning units leads to a 28.4% decrease in annual cooling energy consumption. Collectively, the findings underscore the effectiveness of integrated energy management practices, including optimized building layout, high-efficiency systems, and smart control technologies, in achieving substantial energy savings and operational cost reductions in institutional settings. Full article

The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) in Building Energy Management Systems (BEMSs) offers transformative potential for improving energy efficiency, enhancing occupant comfort, and supporting grid stability. However, the adoption of these technologies in the European Union (EU) is significantly influenced by a complex regulatory landscape, including the EU AI Act, the General Data Protection Regulation (GDPR), the EU Cybersecurity Act, and the Energy Performance of Buildings Directive (EPBD). This review systematically examines the legal, technological, and economic implications of these regulations on AI- and IoT-driven BEMS. Following the PRISMA-ScR guidelines, 64 relevant sources were reviewed, comprising 34 peer-reviewed articles and 30 regulatory or policy documents. First, legal and regulatory barriers that may hinder innovation are identified, including data protection constraints, cybersecurity compliance, liability concerns, and interoperability requirements. Second, technological challenges in designing regulatory-compliant AI and IoT solutions are examined, with a focus on data privacy-preserving architectures (e.g., edge computing versus cloud processing), explainability requirements for AI decision-making, and cybersecurity resilience. Finally, the economic opportunities arising from regulatory alignment are highlighted, demonstrating how compliant AI and IoT-based BEMS can enable energy savings, operational efficiencies, and new business models in smart buildings. By synthesizing current research and policy developments, this review offers a comprehensive framework for understanding the intersection of regulatory requirements and technological innovation in AI-driven building management. Strategies are discussed for navigating regulatory constraints while leveraging AI and IoT for energy-efficient, intelligent building operations. The insights presented aim to support researchers, policymakers, and industry stakeholders in advancing regulatory-compliant BEMS that balance innovation, security, and sustainability. Full article

This study investigates the dynamic relationships between climate change and financial stability in South Africa by employing a Bayesian vector autoregression model (BVAR). Using data from 1991 to 2022, we examine the impact of carbon emissions, adjusted savings, renewable energy consumption, lending interest rates, and unemployment on financial stability. Our findings indicate that carbon emissions, adjusted savings damaged by carbon dioxide emissions, renewable energy consumption, and unemployment significantly erode financial stability. Impulse response functions reveal that shocks to carbon emissions, lending interest rates, and unemployment have lasting effects on financial stability. Forecast error variance decomposition analysis shows that external factors, particularly carbon emissions and lending interest rates, increasingly drive uncertainty in forecasting financial stability over time. The study’s results support the Financial Instability Hypothesis and the Diamond–Dybvig model, highlighting the importance of considering climate-related risks in financial stability analysis. The findings have significant implications for policymakers and financial regulators seeking to promote financial stability and mitigate climate-related risks in South Africa. Full article

Achieving both indoor environmental quality (IEQ) and energy efficiency in school buildings remains a challenge, particularly in older structures where renovation strategies often lack site-specific validation. This study evaluates the impact of energy retrofits on a 1970s primary school in France by integrating in situ measurements with a validated numerical model for forecasting energy demand and IEQ. Temperature, humidity, and CO₂ levels were recorded before and after renovations, which included insulation upgrades and an air handling unit replacement. Results indicate significant improvements in winter thermal comfort (PPD < 20%) with a reduced heating water temperature (65 °C to 55 °C) and stable indoor air quality (CO₂ < 800 ppm), without the need for window ventilation. Night-flushing ventilation proved effective in mitigating overheating by shifting peak temperatures outside school hours, contributing to enhanced thermal regulation. Long-term energy consumption analysis (2019–2022) revealed substantial reductions in gas and electricity use, 15% and 29% of energy saving for electricity and gas, supporting the effectiveness of the applied renovation strategies. However, summer overheating (up to 30 °C) persisted, particularly in south-facing upper floors with extensive glazing, underscoring the need for additional optimization in solar gain management and heating control. By providing empirical validation of renovation outcomes, this study bridges the gap between theoretical predictions and real-world effectiveness, offering a data-driven framework for enhancing IEQ and energy performance in aging school infrastructure. Full article

The present study investigated the influence of a 30 day exposure of rainbow trout (Oncorhynchus mykiss) to a suboptimal low temperature of 1.8 ± 1.0 °C on their different gill characteristics (morphometry, enzyme activities, and expression of genes) in comparison to fish acclimated to 9.4 ± 0.1 °C. Morphometric analysis revealed a significant decrease in the distance between the secondary lamellae at the low temperature, which can be interpreted as a decrease in the effective gill surface. The epithelial thickness increased at the lower temperatures, which is considered a mechanism to reduce ion fluxes and save the energy costs for osmoregulation. The length of the primary lamellae, distance between the primary lamellae, length of the secondary lamellae, as well as the number of mucus cells, chloride cells, and capillaries per mm of the secondary lamella were similar between the temperature regimes. The enzymatic activities of pyruvate kinase and malate dehydrogenase were significantly increased in cold-exposed fish, whereas lactate dehydrogenase activity was higher in controls, indicating increased energy expenditure and adjustments in energy metabolism. The activities of carbonic anhydrase, caspase, Na⁺/K⁺ ATPase, and H⁺ ATPase, and the gene expressions of hif1a, ca2, rhCG, slc26a6, and slc9a1 showed no statistically significant differences between the two temperature regimes. Therefore, it can be concluded that ammonia transport, acid–base regulation, and osmoregulation were not affected by the tested low temperature regime. These findings highlight that exposure to suboptimal temperatures induces structural and metabolic modifications in rainbow trout gills, potentially as an adaptive response to thermal stress. This study contributes to the understanding of fish acclimation to cold environments, with implications for aquaculture and ecological resilience in changing climates. Full article