Search Results (11,214)

The word “energy” is one of the most used in our daily language. People are constantly reminded to save energy, use it efficiently, and increase the use of renewable energy, which is much more environmentally friendly than non-renewable energy. Citizens need to develop a good level of energy literacy, that is, a general predisposition, and, at the same time, a competence for engaging in desirable behaviours in the area of energy consumption. Teachers are a key element in promoting energy literacy. This article aims to compare the energy literacy of first- and third-year students enrolled in the 3 year long Basic Education undergraduate programme of a Portuguese university, who will become primary school teachers. To attain the research objective, 203 prospective teachers (first year: 98; third year: 105) were invited to answer a questionnaire on knowledge about energy (cognitive dimension), behaviour (behavioural dimension) concerning energy, and attitudes (affective dimension) toward energy. Concerning the cognitive dimension, statistically significant differences were obtained between first and third year groups and between third year rural and urban participants; differences between participants with parents with diverse levels of education are not statistically significant. The same applies to comparisons within the affective and the behavioural dimensions. Even though participants seem to believe that they know more than they do, the undergraduate programme in Basic Education seems to cause a small improvement, which is not enough for prospective teachers to reach a good level of energy literacy. Therefore, more attention should be paid to the development, in the Basic Education programme, of energy literacy, considering its diverse dimensions. Full article

The treatment of spent drilling fluids generated during the drilling of technological wells for uranium production represents an important engineering and environmental challenge associated with high energy consumption, significant waste generation, and the need for rational water use under arid regional conditions. Conventional phase separation methods based on gravitational settling and chemical–mechanical treatment are characterized by limited process controllability, long processing times, and increased consumption of reagents and energy. This study proposes an energy-efficient and reliable hydrodynamic technology for the treatment of spent drilling fluids based on the formation of controlled turbulent structures without the use of mechanical drives. The research object comprised spent drilling fluids (SDFs) generated during the drilling of technological wells for uranium production in the southern regions of the Republic of Kazakhstan and the Kyzylorda region. Experimental investigations were carried out using a laboratory–pilot hydrodynamic disperser with variations in velocity gradient, treatment time, flocculant dosage, and suspension flow rate. A mathematical model linking hydrodynamic process parameters with phase separation kinetics and energy characteristics was developed. Model calibration by weighted nonlinear least squares yielded a stable parameter set with 95% confidence intervals, and model validation demonstrated good agreement between calculated and experimental data (MAPE 8.4%; maximum relative error 11.8%). It was established that the use of a hydrodynamic disperser provides separation efficiency of up to 90–95% under optimal operating conditions while reducing specific energy consumption and maintaining stable repeated-cycle performance within the investigated operating window. Experimental results confirm that implementation of the hydrodynamic technology enables a reduction in sludge volume by 40–60%, recovery of up to 60–80% of process water, and a significant decrease in waste requiring transportation and disposal. The obtained results demonstrate the high environmental and resource-saving efficiency of the proposed technology and its suitability for scaling and industrial implementation at facilities drilling technological wells for uranium production. The developed hydrodynamic approach can be considered an effective engineering platform for creating energy-efficient and sustainable systems for drilling fluid treatment in regions with limited water resources and remote industrial infrastructure. Full article

Against the backdrop of rising environmental pressure and increasing reliance on supply-chain-based governance, this study examines the environmental impact of China’s Green Supply Chain Management Demonstration Program. Using a panel of Chinese listed firms from 2012 to 2024, I exploit the inclusion of firms in the government-designated demonstration list as an exogenous policy shock and estimate its effects within a difference-in-differences framework. The results show that participation in the program significantly improves corporate environmental performance. Treated firms are more likely to adopt environmentally friendly practices, including renewable energy use, circular economy initiatives, and energy-saving technologies, and are more likely to receive environmental awards and other forms of positive environmental recognition. Mechanism analyses suggest that these effects operate through increased green patenting activity and enhanced environmental information disclosure quality. Heterogeneity analyses indicate that the effects are stronger for firms with higher supply chain efficiency, more limited access to external resources, and lower pre-existing green innovation, as well as for state-owned enterprises, firms located in eastern China, and those benefiting from greater government green support. Overall, the findings provide causal evidence that supply-chain-oriented environmental policies can effectively enhance corporate environmental performance in emerging economies Full article

Moving toward sustainable energy in small-scale dairies is an indispensable requirement and a significant challenge in developing countries. This study investigates a solar-powered refrigeration system with heat recovery designed to address the energy challenges faced by small-scale dairy farmers in off-grid areas of developing nations. It presents a novel solar-powered refrigeration system with integrated heat recovery, experimentally optimized to simultaneously deliver heating and cooling while valorizing waste heat and synergistically integrating solar energy to establish a decentralized and energy-autonomous milk preservation system for off-grid applications. The proposed system successfully recovers an average of 55% of the heat rejected by the condenser, thereby delivering more than 1000 W of usable thermal energy necessary for milk pasteurization. The experimental findings showed a coefficient of performance of 4.7, representing a 43% improvement over conventional systems, and achieved a Carnot efficiency of 42%. In addition, the system yields an annual energy savings of 3650 kWh and reduces carbon emissions by 971 kg per year for a 50 L unit. These findings underscore the system’s substantial potential to enhance energy efficiency, promote sustainability, reduce spoilage, improve incomes, mitigate carbon emissions, and enhance local milk preservation capabilities within small-scale dairy operations, minimizing reliance on diesel or firewood, particularly in regions that are distant from access to grid energy. Full article

As the boundary between indoor and outdoor spaces, the heat flux of a building envelope is a crucial factor influencing the indoor thermal environment and human thermal comfort, and also an important indicator reflecting the impact of outdoor meteorological factors on the indoor environment. In scenarios involving rapid assessment of existing buildings and engineering projects, the dynamic thermal performance of the building envelope are often affected by factors such as outdoor weather fluctuations, window–wall coupling, wall heat storage, and thermal bridging. To address this issue, this study proposes a dynamic heat flux calculation method that accounts for hysteresis. Simultaneously, the heat conduction equation of the implicit finite difference method (IFDM) and boundary conditions based on wall energy balance are used to optimize the wall surface temperature. An adaptive step size control strategy (Runge–Kutta–Fehlberg) is introduced in the time step setting. Results show that the heat flux R² of the proposed dynamic heat flux calculation method is 0.9207, and the optimized R² is 0.9435, both within an acceptable range for engineering applications. Studies have shown that the simplified framework derived from the heat flux analysis of building envelopes retains the characteristics of wall heat storage and delayed heat release, while effectively solving the window–wall coupling problem and significantly reducing the reliance on computationally expensive numerical methods. This method therefore provides an efficient and scalable technical pathway for thermal performance assessment and energy-retrofit decision support for existing building envelopes. Full article

The retrofit of existing residential buildings plays a critical role in reducing energy consumption and carbon emissions in the building sector. However, previous retrofit evaluations often fail to account for the age-related thermal and lighting requirements of residents in aging residential buildings, thereby overlooking the substantial behavioral heterogeneity that shapes retrofit effectiveness. This study evaluates the comprehensive performance of different building envelope retrofit strategies, considering occupants’ thermal and visual comfort, from the perspectives of energy efficiency, economic feasibility, and environmental sustainability. First, age-specific differences in occupancy patterns, thermal preferences, and lighting requirements between elderly and non-elderly comparison group occupants were systematically extracted from the literature. Then, a typical high-rise residential building was modeled in EnergyPlus to serve as the reference building, within which the differentiated occupant behavior models were implemented, and the pre-retrofit condition was defined as the baseline scenario. Next, six commonly applied exterior wall insulation materials and different glass configurations and window frames were parameterized and evaluated under varying insulation thicknesses and remaining building service life scenarios. Finally, the energy-saving performance, economic benefits, and carbon reduction potential of envelope retrofit measures were quantitatively assessed across three primary functional zones (bedroom, living room, and study), using area-normalized indicators. The results indicate that, in the retrofit of existing residential buildings, bedrooms and study rooms exhibit greater retrofit benefits than living rooms, primarily due to longer occupancy durations and higher heating demand. In terms of retrofit strategies, exterior wall insulation consistently outperforms window retrofitting in energy-saving potential, with energy-saving rates of approximately 3.2–4.3% depending on functional zone, material type, and insulation thickness. Among the evaluated materials, vitrified microbead insulation performs best overall in terms of energy, economic, and carbon benefits at 40–60 mm thickness. These findings support occupant-informed, low-carbon retrofit decision-making for existing residential buildings. Full article

Heavy-duty forklifts possess substantial kinetic energy during braking, which is currently wasted due to a lack of recovery in conventional systems. To ensure braking safety, an electro-hydraulic–mechanical compound braking system is necessary. However, the uncoordinated distribution between regenerative and mechanical braking torque leads to braking torque fluctuations, compromising safety, comfort, and recovery efficiency. This paper constructs a parallel hydraulic hybrid power system for heavy-duty forklifts based on a four-quadrant pump/motor, enabling braking energy recovery and reuse via the pump/motor and an accumulator. A compound braking strategy based on the ideal braking force distribution and multi-sensor information fusion is proposed. The system incorporates various sensors, including pressure, speed, flow, and pedal displacement sensors, to monitor system status and driver intention in real time, providing precise data for coordinated control. Feasibility is verified through AMESim simulation and real vehicle tests. The control system based on sensor feedback maximizes braking energy recovery while ensuring braking safety and comfort, achieving a 12.2% energy-saving rate and significantly improving the vehicle’s economy and range. Full article

Understanding the socio-demographic drivers of residential energy-saving behavior is critical for designing effective energy policies and technologies. This study applies a Multiple Indicators, Multiple Causes (MIMIC) model to examine how individual characteristics are associated with two latent constructs: energy concern and smart-home interest and usage. Using survey data collected from urban residents in Guangdong Province (N = 261), structural equation modeling was employed to assess both measurement and structural components of the model. The results show that income is positively associated with both energy concern and smart-home interest and usage, whereas being a bill payer is negatively related to both. Gender also plays a role, with females reporting higher energy concern. Other factors, such as age, education, and time spent at home, did not show significant effects. The model showed acceptable global fit indices; however, the reliability and convergent validity of the latent constructs were limited. Accordingly, the findings should be interpreted as exploratory associations observed within this sample and may serve as a basis for future research on segmentation in similar urban contexts. Full article

The International Maritime Organization’s (IMO) greenhouse gas (GHG) strategy aims for a 40% reduction in carbon intensity by 2030 and a 70% reduction by 2050, relative to 2008 levels. Attainment of these objectives necessitates an integrated strategy encompassing technological advancements, operational optimization, and the adoption of innovative practices to curtail fuel consumption and enhance vessel performance. The Ship Energy Efficiency Management Plan (SEEMP), mandated by MEPC 62 in 2011, establishes a systematic framework for the continual enhancement of energy efficiency. SEEMP is intrinsically associated with reductions in fuel consumption, enabling maritime organizations to systematically monitor and control energy performance via the Energy Efficiency Operational Indicator (EEOI). This metric enables operators to assess operational energy performance and implement measures such as optimized voyage planning and fuel-saving technologies. However, the effectiveness of SEEMP varies widely across companies and vessel types, often due to limited crew awareness. To enhance daily implementation, it is essential to improve crew training and streamline SEEMP documentation. Simplifying SEEMP structures within ship management companies can further facilitate usability and compliance. By focusing on these areas, the maritime industry can better align with IMO’s GHG reduction targets and promote more sustainable operations and fuel-saving technologies. Full article

This research investigates the influence of economic, energy, and institutional variables on sustainable economic growth for Pacific Asian countries using Adjusted Net Savings (ANS) as a more refined measure of sustainable development. Using an unbalanced panel dataset for the period 1996 to 2021, second-generation panel data analysis is conducted to capture both long-run and distributional relationships, addressing potential concerns about cross-sectional dependence. The results indicate the presence of long-run relationships that are stable for both sustainable development itself and for its defining factors. Foreign direct investments (FDI) are found to have the most significant influence on sustainable development for all quantile values, underlining their central importance to long-run capital accumulation efforts. Renewable energy consumption helps increase sustainability outcomes for countries with lower savings performance values, while renewable energy production is found to have a modest but positive influence for each quantile of the distribution of outcomes. Natural resource wealth is seen to have non-linear effects on outcomes, with countries with lower savings values being adversely affected, while countries with higher savings values are beneficially affected. The presence of institutional factors is an enabler for countries with lower values of sustainable development performance. Full article

With the widespread adoption of electric vehicles (EVs), the management and scheduling of charging and discharging play a crucial role in the performance of both the electricity grid and electric vehicles. Particularly in the context of peak shaving, valley filling, and the promotion of the energy internet infrastructure, efficient management of the EV charging and discharging process is vital. This study investigates the control and management issues surrounding EV charging and discharging, proposing a management strategy based on deep reinforcement learning. By constructing an intelligent decision-making model, it integrates factors such as the operating conditions of the electrical grid, user behavioral preferences, EV battery characteristics, and renewable energy outputs. The study collects real-world EV usage data from a city, establishing an experimental environment to simulate the interaction between the electricity grid and electric vehicles. Using techniques such as Deep Q-Network (DQN) and policy gradients, it constructs a decision network to explore charging and discharging strategies across different time scales and load situations. Experimental results show that this strategy, compared to traditional charging schedule methods, can effectively reduce energy loss during charging, enhance battery life, and balance the grid load, while suppressing demand peaks, thus achieving intelligent optimization and reliability enhancement of the charging and discharging process. Particularly, an adaptive charging power adjustment technique within the strategy can dynamically adjust the charging power according to the real-time status of the EV and grid load without affecting the user’s daily use, thereby achieving the dual objectives of efficient energy saving and economy. The research also quantitatively analyzes battery degradation characteristics and the continuity of charging to ensure the long-term sustainability of the charging strategy. The research findings are significant for understanding and guiding the practical management of EV charging and discharging. Full article

Conservation easements (CEs) represent a complex policy instrument designed to mediate the feedback loops within coupled human and natural systems in protected areas. However, their efficacy is often constrained by a lack of systemic understanding of the localized drivers of community support. Building upon the successful implementation of Forest Land Easements (FLEs) within China’s Qianjiangyuan National Park Pilot, this study investigates the potential to expand this policy model to other land types. This study investigates the multilevel factors influencing residents’ willingness to adopt three types of CEs, including forest land (FLE), agricultural land (ALE) and homestead land (HLE) easements in China’s Qianjiangyuan National Park Pilot, the country’s primary CE reform site. We conceptualize a hierarchical support model wherein community participation (CP) and human well-being (HW) interact with support for park management (SM), forming a subsystem that drives decisions within the broader land-use. Utilizing structural equation modelling (SEM) and stepwise regression analysis on survey data from 336 households, we tested this model. The results reveal that SM acts as a critical direct mediator and positive driver of CE acceptance, while CP and HW exert significant indirect effects through SM, demonstrating a key feedback pathway. Regression analyses further elucidate that support for different CE types is driven by distinct configurations of factors, highlighting the heterogeneous nature of subsystems. Notably, livelihood benefits and prior participation experiences emerged as consistent, cross-cutting systemic leverages. It demonstrates that leveraging the implementation experience and community support gained from existing forest land easements is crucial. This study concludes that effective CE design must move beyond one-size-fits-all approaches. It necessitates differentiated, adaptive policies that are coherently aligned with local livelihood subsystems and strategically strengthen participatory feedback mechanisms initiated by successful FLEs. Our findings provide an evidence-based framework for designing resilient, socially sustainable conservation policies in complex protected area systems, grounded in proven practice. Full article

Residential photovoltaic/thermal (PV/T) systems can reduce electricity consumption by supplying both electricity and heat; however, their performance depends on household composition and lifestyle-driven demand profiles. This study simulates a PV/T system for a detached house in Tokyo while accounting for occupant-behavior variability using Japanese time-use statistics from 2015 and 2020, which capture the pandemic-related increase in time spent at home in 2020. Both a PV/T system and a conventional PV system were evaluated for four representative household scenarios, reflecting changes in domestic hot water (DHW), space conditioning, and appliance electricity demand. In the 2020 dataset, the large-household case (Case C) showed the largest improvement in net electricity balance relative to the PV system, with an improvement of 1.8 GJ, while the elderly-couple case (Case D) achieved the highest overall thermal efficiency, with a DHW COP of 6.26 and a space-heating COP of 5.75. In the young-couple case (Case A), the CO₂ reduction increased from 169 kg in the 2015 dataset to 239 kg in the 2020 dataset, showing that lifestyle changes affected the energy-saving benefit. These findings indicate that lifestyle-dependent behavioral changes should be considered in PV/T performance assessment and system sizing. Full article

This study quantitatively evaluates the effect of solid-phase pre-reduction of chromite concentrate on the energy efficiency and techno-economic performance of high-carbon ferrochrome (HC FeCr) smelting. Laboratory pre-reduction experiments were conducted at 1200–1400 °C using Shubarkol coal, metallurgical coke, and special coke as carbonaceous reducing agents. Structural and phase transformations were characterized by X-ray diffraction (XRD) and scanning electron microscopy with energy-dispersive spectroscopy (SEM-EDS). At 1200 °C, the degree of metallization remained low (<5%), whereas at 1400 °C it increased to 41.3% under laboratory conditions and up to 65% in pilot-scale tests due to the decomposition of the spinel matrix and the formation of metallic and carbide phases. The application of pre-reduced feedstock in a submerged arc furnace reduced specific electricity consumption by up to 33.5% compared with conventional smelting and increased chromium recovery to 89.71%. Industrial-scale extrapolation indicates the potential to decrease power consumption to approximately 3190 kWh/t of alloy. Techno-economic analysis demonstrates that the use of pre-reduced feedstock reduces the production cost by approximately 10–23%, depending on the type of carbonaceous reducing agent (Shubarkol coal, metallurgical coke, or special coke). Special coke provided the highest energy efficiency, whereas Shubarkol coal ensured the greatest direct economic benefit. The integrated microstructural, energetic, and economic assessment confirms the industrial applicability of the proposed pre-reduction approach. Full article

This paper proposes a physics-informed hybrid digital CO₂ emission-control technology for maritime transport, designed for adaptive ship speed optimization along a predefined geographical route between two ports, discretized into quasi-stationary segments and evaluated under forecasted metocean conditions, subject to economic and regulatory constraints associated with maritime decarbonization. The framework integrates two exact optimization methods, Backtracking (BT) and Dynamic Programming (DP), with a reinforcement learning approach based on Proximal Policy Optimization (PPO), operating on a unified physical, economic, and regulatory modeling core. By reducing propulsion fuel demand, the system acts as an upstream CO₂ emission-control mechanism for ship propulsion. This operational stabilization of the engine load creates favourable boundary conditions for advanced combustion processes and reduces the volumetric flow of exhaust gas, thereby lowering the technical burden on potential post-combustion carbon capture systems. Segment-wise speed profiles are optimized subject to propulsion limits, Estimated Time of Arrival (ETA) feasibility, and regulatory constraints, including the Carbon Intensity Indicator (CII), the European Union Emissions Trading System (EU ETS) and FuelEU Maritime. The physics-based propulsion and energy model is validated using full-scale operational data from four real voyages of an oil/chemical tanker. A detailed case study on the Milazzo–Motril route demonstrates that adaptive speed optimization consistently outperforms conventional cruise operation. Exact optimization methods achieve voyage time reductions of approximately 10% and fuel and CO₂ emission reductions of about 9–10%. The reinforcement learning approach provides the best overall performance, reducing voyage time by approximately 15% and achieving fuel savings and CO₂ emission reductions of about 13%. At the route level, the Carbon Intensity Indicator is reduced by approximately 10% for the exact methods and by about 13% for PPO. Backtracking and Dynamic Programming converge to nearly identical globally optimal solutions within the discretized decision space, while PPO identifies solutions located on the most favourable region of the cost–time Pareto front. By benchmarking reinforcement learning against exact discrete solvers within a shared physics-informed structure, the proposed digital platform provides transparent validation of learning-based optimization and offers a scalable decision-support technology for pre-fixture evaluation of fixed-route voyages. The system enables quantitative assessment of CO₂ emissions, ETA feasibility, and regulatory exposure (CII, EU ETS, FuelEU Maritime penalties) prior to transport contracting, thereby supporting economically and environmentally informed operational decisions. Full article