Search Results (409)

Indonesia has significant fisheries potential; however, limited cold chain infrastructure at small-scale fishing ports contributes to post-harvest losses and quality degradation of fishery products. This study presents the design and techno-economic assessment of a modular portable cold storage unit for tuna fisheries integrated with renewable energy systems. The system (7 × 3 × 5 m) uses polyurethane sandwich panels and requires a maximum cooling load of 6.14 kW with peak power consumption of 7.93 kW. The estimated capital cost is approximately USD 34,100, while the operational cost is about USD 198 per cycle. A comparative analysis using the Levelized Cost of Energy (LCOE) method indicates that diesel generators provide the lowest cost at approximately USD 0.56/kWh, whereas standalone photovoltaic (PV) systems exhibit the highest cost at around USD 0.89/kWh. However, hybrid PV systems offer the best balance between cost efficiency and environmental performance by reducing carbon emissions. The results demonstrate that integrating hybrid renewable energy into modular cold storage enhances cold chain reliability, reduces fish losses, and supports sustainable coastal development. This approach contributes to low-carbon fisheries infrastructure and aligns with global sustainability and renewable energy transition goals. Full article

PV/T collectors and Air Source Heat Pump (ASHP) are widely studied for building heating, but solar intermittency and ASHP low-temperature frosting limit their large-scale deployment. A novel PV/T-ASHP coupled heating system is proposed to cut building carbon emissions and relieve ASHP performance degradation in cold zones. Circulating water cools PV/T panels to boost power generation, and the warmed water preheats ASHP evaporator inlet air to reduce frosting and defrosting frequency. With a Xi’an office building as the research object, validated TRNSYS 18.0 models are established for comparative analysis with conventional systems and cross-climate evaluation in Xi’an, Beijing, Shanghai and Chengdu. Results show the new system lifts PV/T combined efficiency by 17.56%, reduces energy consumption by 19.9%, and achieves an average COP of 3.2. Across climate zones, its COP rises 11.5–24.6% and 50-year carbon emissions fall 16.4–26.2%, supporting low-carbon heating promotion for office buildings. Full article

A solar cooling facility with two forms of energy storage, electrochemical (batteries) and thermal (tanks containing the heat transfer fluid, HTF), is simulated. The technical specifications used in the simulation are taken from a recently installed system in an institutional building at the University of Almería (Spain). Electricity generated by photovoltaic (PV) panels is either stored in a battery bank, or supplied directly to the chiller, which is also connected to the grid as a backup. The HTF circulates through a storage tank and is driven to a heat exchanger to cover the refrigeration demand. The whole system is modeled in TRNSYS with the corresponding meteorological data: the PV array has a peak power of 23.4 kW, the compression chiller power is 70 kWt, and the building demands of refrigeration from high and low season amount to 413.5 kWh/day and 62.8 kWh/day, respectively. The battery bank capacity is 40.8 kWh and the tank has a volume of 4000 L. Different configurations of energy storage (only electrical, only thermal, and hybrid) are tested for both demands. The results show that the refrigeration needs can be covered with solar energy and storage in the low season, with a surplus that can be driven to the building. In the high demand season, an extra input from the grid is needed as the current facility covers 89.3% of the total electricity requirements per day (54.5% if no storage is used). Finally, the system performance is evaluated over an intermediate-demand month. Overall, it is found that electrical consumption from the grid is minimal when batteries are used, either alone or in conjunction with thermal storage. Full article

This paper estimates end-use demand elasticities for European Union residential energy consumption and applies them to projections of household energy demand up to 2030 and 2050. Using a 2013–2023 panel for the EU27, we estimate country fixed-effects demand equations with Driscoll-Kraay standard errors for total household energy and five Eurostat end-use categories: space heating, space cooling, water heating, cooking, and lighting and appliances. The explanatory variables are heating and cooling degree days, real household electricity and gas prices, and real GDP per capita. The estimated elasticities are applied to six scenarios that combine two climate trajectories with three energy-price pathways, calibrated to international policy scenarios. These pathways are price approximations of the corresponding IEA scenarios; technology, electrification, and fuel-mix transformations are not modeled. We also examine stylized Renovation Wave sensitivities that impose reductions of 20%, 40%, and 60% in projected space-heating energy demand. The results show that EU27 residential energy demand is projected to fall by 2% to 12% by 2050 across the six scenarios, mainly because of reductions in heating demand, which dominate increases in cooling demand in absolute energy terms. Under the central scenario, total demand falls by 4.0%. Renovation sensitivities imply substantially larger reductions, ranging from 17% to 40%. The findings highlight the importance of building-envelope improvements, cooling-related adaptation, and end-use heterogeneity in long-run residential energy-demand policy. The paper contributes a harmonized end-use projection framework that links climate exposure, household energy prices, income, and building-envelope efficiency within a single empirical model of EU residential energy demand. Full article

Direct hot press forming (DHPF) of Zn-coated press-hardening steel (PHS) has not been widely adopted by industry due to liquid metal embrittlement (LME), which occurs when coated steel is hot stamped above the Fe-Zn peritectic temperature (~782 °C). In the present study, low-temperature hot stamping was performed on a 2.0 wt% Mn PHS to avoid LME by preventing liquid zinc formation during plastic deformation while achieving target mechanical properties (yield strength (YS) ≥ 1100 MPa and ultimate tensile strength (UTS) ≥ 1500 MPa) and preserving corrosion performance. The enhanced hardenability, indicated by a critical cooling rate (CCR) of 10 °C/s, enabled a predominantly martensitic microstructure following DHPF at 550–700 °C. Tensile testing of samples extracted from U-shaped panels yielded similar results for uncoated and Zn-coated samples, with a YS of ~1170 MPa, a UTS of ~1600 MPa, a uniform elongation (UE) of 0.05, and a total elongation (TE) of 0.09, demonstrating the preservation of baseline mechanical properties in the coated samples. Microstructural analysis confirmed the absence of LME-induced substrate cracking. Additionally, XRD, SEM-BSE, and EDS analyses confirmed Γ-Fe₃Zn₁₀ formation in DHPF galvanized coatings, with volume fractions averaging ~0.6, well above the critical value of 0.15, irrespective of the DHPF temperature, demonstrating the formation of a cathodically protective coating microstructure. Full article

Artificial intelligence-integrated ‘buy now, pay later’ (BNPL) platforms are diffusing rapidly across the Middle East and North Africa (MENA), raising concerns about consumer financial vulnerability. Drawing on choice architecture, payment decoupling, and financial literacy literatures, this study examines how three platform-level features—algorithmic nudging, AI personalization intensity, and perceived ease of credit—are associated with impulsive buying tendency and downstream financial outcomes, and whether BNPL-specific financial literacy attenuates these associations. A multi-method design combined cross-sectional partial least squares structural equation modeling (N = 1247 active BNPL users in seven MENA countries) with a six-month longitudinal follow-up (N = 847, 68% retention). Algorithmic nudging was positively associated with impulsive buying tendency, which in turn was associated with elevated financial stress and longitudinal debt accumulation. The ‘loyalty trap’—a paradoxical state in which financially stressed consumers maintain high platform loyalty—is provisionally documented via piecewise longitudinal trajectories. We emphasize that this pattern is consistent with but not causally established by the present design, and we outline specific experimental and quasi-experimental research designs needed for causal identification. BNPL-specific financial literacy moderated the associations between algorithmic nudging, impulsive buying, and adverse financial outcomes, with the highest-literacy quartile exhibiting substantially attenuated debt trajectories. We discuss boundary conditions, alternative explanations, and the limits of causal inference in non-experimental panel data. Findings inform evolving BNPL regulatory frameworks in MENA, with particular relevance to nudge-transparency disclosures, contractual cooling-off periods, and credit-bureau reporting standards. Full article

The optimal control of complex energy systems via Bellman’s principle of optimality quickly becomes difficult for high-dimensional, path-dependent dynamics because the state space grows exponentially with each time step. We propose a computationally tractable framework based on hierarchical path-dependency decomposition: (i) graph compression that reduces multi-layer topologies to a single directed flow network; (ii) a diffusion convolutional recurrent neural network (DCRNN) that maps historical trajectories into a finite-dimensional hidden state, approximating the transport of past states without storing full trajectories; and (iii) multi-agent reinforcement learning (MARL) for decentralized local control. By restricting full-path online optimization to a rolling one-step horizon and using temperature and flow rate as sufficient statistics for thermal dynamics, the framework preserves physical fidelity while enabling real-time execution. This reduction is justified because thermal constraints constitute the primary active failure mode in energy systems. We provide a proof sketch showing that the diffusion convolution operation in the DCRNN approximates the Green’s function of the underlying transport equation. Using weather data from Palm Springs, California (a region with moderate path dependency), initial numerical experiments achieve 98.4% correlation with reference solutions, a temperature forecasting mean absolute error (MAE) of 1.23 °C, and mostly subsecond (<1 s) inference times using consumer-grade hardware. Despite the thermodynamic advantages of concentrated solar thermal (CST) systems over conventional photovoltaic panels—higher conversion efficiency and integrated thermal storage—their deployment on factory rooftops remains elusive due to the continuous, real-time control burden they impose. The proposed framework directly addresses this barrier by delivering accuracy comparable to classical controllers (MPC, PID) with latency sufficient for real-time intervention, positioning CST for transition from remote desert locations to distributed industrial sites. Beyond solar-thermal generation, the same hierarchical architecture is applicable to integrated HVAC system control (e.g., using movable mirrors to both produce renewable energy and reduce cooling loads in data centers), energy storage management, desalination plant control, and chemical production optimization—any domain where thermal-hydraulic transport must be regulated under tight safety and latency constraints. The framework demonstrates that trading exact Bellman optimality for data-driven approximations enables a shift from offline simulation to sensor-driven real-time regulation across this broader class of energy systems. Full article

The energy management (EM) of smart multi-carrier energy hub (SMCEH) systems for cost and emission reduction remains a challenging problem due to the diversity of renewable energy resources (RERs), varying load demands, and the stochastic nature of these resources. This paper addresses the EM problem of SMCEHs to minimize operational costs and greenhouse gas (GHG) emissions using the particle swarm optimization (PSO) algorithm. The studied SMCEHs are designed to simultaneously supply electrical, cooling, and thermal demands. The hub system comprises wind turbines (WTs), photovoltaic (PV) panels, gas turbines (GT), electric chillers (EC), gas boilers (GBs), absorption chillers (AC), battery storage systems, and thermal storage units. To assess system performance and the impact of key technologies, three case studies are investigated: (i) EM of SMCEHs without RERs, (ii) EM of SMCEHs with RERs, and (iii) EM of SMCEHs with RERs and an integrated carbon capture unit (CCU). These scenarios enable a systematic evaluation of the role of renewable integration and carbon capture in enhancing system performance. The results demonstrate that incorporating RERs into SMCEHs leads to a substantial reduction in both operational costs and GHG emissions. Furthermore, the integration of a CCU provides additional emission reductions, underscoring its effectiveness in supporting the low-carbon operation of SMCEHs. The obtained results show that integrating RERs into SMCEH decreases the total cost and emissions by 64.12% and 7.95%, respectively, compared to the scenario without RERs. Furthermore, the integration of the CCU into SMCEHs provides a 39.36% reduction in total costs and a 72.57% decrease in CO₂ emissions. The suggested energy management solution promotes a sustainable and low-carbon emission system by maximum utilization of the RERs and CCU. Full article

Urban canopy mitigates urban heat, yet how the spatial configuration of high- and low-canopy layers shapes population heat exposure across a national urban system remains insufficiently understood. Drawing on a panel of 369 Chinese prefecture-level cities for 2000, 2005, 2010, 2015, and 2020, this study constructs a population-weighted thermal-exposure metric—the Human Heat Exposure Index (HEI)—and stratifies urban vegetation into high- and low-canopy classes based on Chinese Land Cover Dataset (CLCD) land-cover types. Multiscale Geographically Weighted Regression (MGWR) and Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP)-based interpretation are combined to identify spatially varying associations and nonlinear marginal effects of stratified canopy patterns on HEI. HEI shows a persistent south–high, north–low spatial structure, with Global Moran’s I stable at approximately 0.85 throughout the study period. High-canopy edge density and cohesion are increasingly associated with reduced heat exposure in densely built regions, while low-canopy mean patch area and edge density retain explanatory power across all years through near-surface evapotranspirative regulation. The marginal cooling effect of vegetation strengthens appreciably only above an Normalized Difference Vegetation Index (NDVI) of approximately 0.6, and the apparent inflection ranges for impervious surface proportion and standardized solar radiation lie near 25% and 0.4, respectively. These findings suggest that in cities with high impervious loads, cooling-network connectivity and within-zone canopy configuration matter more than additional canopy area alone, and that planning targets should be calibrated to climate zone, city type, and existing surface conditions. Full article

In this study, an experimental investigation was conducted to evaluate the thermal and electrical behavior of three photovoltaic panel configurations under controlled indoor solar irradiation of 600, 800, and 1000 W/m², considering both natural and forced convection to the surrounding air. The tested configurations included an uncooled reference panel (PV-1), a PCM-cooled panel incorporating a flat rear container (PV-2), and a proposed PCM-cooled panel equipped with an extended-surface rear container (PV-3). A PCM characterized by a phase change temperature range of 41–48 °C was employed. The results showed that the extended-surface PCM configuration associated with PV-3 provides a more effective passive cooling solution compared to the flat container design. Under natural convection, this thermal advantage of PV-3 became more pronounced, with a maximum temperature reduction of 15 °C at 1000 W/m² after 170 min of operation, compared to PV-2. Consequently, PV-3 achieved the highest electrical performance, delivering peak efficiency enhancements of 12.05% and 7.38% relative to PV-1 and PV-2, respectively, and average efficiency gains of 7.06% and 5.35% over the entire test period. Under forced convection, however, performance differences among the configurations were minimal because forced convection dominated the heat removal process, reducing the influence of the PCM. Full article

Electric vehicle (EV) transport by ship is expanding beyond industrial logistics centred on automobile production, trade, and pure car and truck carriers (PCTCs) into daily transportation for island tourism, commuting, and essential mobility. According to Korea Maritime Transportation Safety Authority (KOMSA) vessel status data as of March 2026, 104 of 146 domestic passenger ships were car-ferry passenger ships, accounting for 71.2% of the fleet and operating on 75 of 99 designated routes nationwide. Korea Shipping Association (KSA) operational records show that the EV transport rate on these routes increased from 0.76% in 2024 to 1.21% in 2025, with some routes exceeding 2.0–4.7%. Unlike enclosed multi-deck PCTC vehicle spaces, Korean coastal car-ferry passenger ships generally have single-tier open vehicle decks and bow ramp gates. Crosswinds on open decks may reduce smoke detector activation probability by 60–75%. Although Article 97 of the Standard for Ship Fire-Fighting Appliance newly requires dedicated EV fire-fighting equipment for car-ferry ships, it remains primarily equipment-prescriptive and does not yet provide open-deck-specific performance requirements for wind-resistant detection, fixed EV-zone cooling, EV-designated stowage arrangements, or passenger–operator safety management obligations. This study applies the five-step International Maritime Organization (IMO) Formal Safety Assessment (FSA) procedure to support improvements to EV fire-fighting equipment standards for coastal car-ferry passenger ships. Hazard identification (HAZID) was conducted with a 15-member advisory panel, and probability elicitation was performed through a Delphi survey with 10 core experts, showing strong consensus (Kendall’s W = 0.74, p < 0.01). Fault tree analysis (FTA) and event tree analysis (ETA) probabilities were derived from the Delphi results and the international literature. H-07, representing wind-induced smoke dilution, was identified as the dominant single-point vulnerability within the detection-failure branch. Monte Carlo-based FTA–ETA analysis (n = 10,000) estimated annual fire frequencies of 5.9 × 10⁻², 1.8 × 10⁻¹, and 2.9 × 10⁻¹ yr⁻¹ at EV loading ratios of 10%, 30%, and 50%, respectively, with 2.47 expected fatalities per fire. Risk entered the IMO ALARP band above a 30% EV loading ratio and exceeded the maximum tolerable crew risk above 50%. The combined application of risk control options (RCOs) 2, 3, and 4 reduced annual expected fatalities by 85.6%. Based on these results, six RCOs and institutional recommendations are proposed, including strengthened safety management obligations for passenger ship operators. Full article

This paper presents a parametric numerical study on the cooling performance of photovoltaic panels using water and an Al₂O₃-based nanofluid. The increase in operating temperature leads to a decrease in electrical efficiency, making thermal management a key factor in optimizing these systems. The analysis was carried out through numerical simulations in ANSYS, aiming to evaluate the influence of volumetric flow rate and inlet temperature of the cooling fluid on the panel cooling time under transient conditions. The results show that the performance of the Al₂O₃ nanofluid depends on the flow rate of the cooling fluid. At a low flow rate of 0.05 m³/h and a concentration of 4%, the cooling time is reduced by approximately 18–22% compared to water, while this advantage diminishes as the flow rate increases. A favorable operating region was also observed within the investigated laminar and near-transitional range, beyond which increasing the flow rate produced only limited additional reductions in cooling time under the assumptions of the numerical model. The findings highlight the importance of correlating the thermophysical properties of the fluid with flow parameters in order to optimize the thermal management of photovoltaic panels. Full article

This study critically addresses the challenge of selecting optimal insulation materials for contemporary, energy-efficient building envelopes, a decision with profound environmental, structural, and occupational health consequences. The paper responds to the growing demand for sustainable, resilient solutions by comparing wool, a bio-based, regenerative material, and expanded polystyrene (EPS), a synthetic polymer widely implemented in the construction industry, and advanced laboratory testing (thermal conductivity, moisture buffering, freeze–thaw resistance) is discussed in a comprehensive synthesis of the recent literature. Also, field evaluations from European retrofits and pilot projects (UK, Denmark, Finland, Iceland, Norway, Sweden, Germany and France) further contextualize performance outcomes, and life cycle impacts are considered. Recent results reveal that wool insulation achieves a moisture buffering value (MBV) between 1.8 and 2.7 (g/m²) % RH, minimal vapor resistance (mvr = 1–2), and preserves functional and structural integrity through more than 100 freeze–thaw cycles, leading to significant stabilization of the interior microclimate and enhanced durability. In contrast, EPS delivers lower thermal conductivity (0.032–0.037 (W/mK), critical for reducing heating/cooling demand, but exhibits limited vapor permeability (lvp = 60–150 MN·s/(g·m)), increased risk of condensation and mold, and reduced compressive strength (<22% after 30 cycles), especially when ventilation details are inadequate. Hybrid envelope systems leveraging both EPS and wool are demonstrated to optimize energy efficiency (up to 23% seasonal savings) and reduce interior humidity fluctuations, while lifecycle and recycling assessments show wool panels to be markedly superior in carbon footprint reduction and circularity. The stratification of insulation layers incorporating wool for vapor and moisture control, and EPS for pure thermal resistance is emerging as best practice in sustainable retrofit and new-build projects. Recommendations highlight the necessity for rigorous laboratory validation, international standards alignment, and integrated material design for robust hygrothermal comfort and environmental performance. The review also covers wool- and EPS-based hybrid composites, showing how natural fibers can improve key mechanical properties without compromising thermal insulation performance or environmental benefits. Full article

Respiratory mortality in Europe is associated with interacting environmental, infrastructural, climatic, and energy-related conditions. This study investigates country–year patterns of respiratory disease mortality by integrating panel-data econometrics, clustering analysis, and machine-learning prediction. The econometric results indicate that agricultural land use and coal-based electricity generation are positively associated with respiratory mortality, while access to electricity and freshwater withdrawals show negative associations. Cooling degree days capture a heat-related environmental-health dimension, although some coefficients become weaker under robust specifications. Sanitation and renewable energy display heterogeneous and specification-sensitive patterns, suggesting that they may partly reflect broader development gradients, infrastructure transitions, and regional heterogeneity rather than direct causal mechanisms. Hierarchical clustering identifies 10 country–year environmental-health profiles, highlighting differentiated combinations of energy systems, land use, infrastructure, climatic exposure, and respiratory mortality. This approach avoids treating countries as fixed homogeneous units and allows environmental-health profiles to vary over time. The selected hierarchical solution provides a balanced and interpretable structure relative to more polarized clustering alternatives. Machine-learning models are used as a complementary predictive exercise rather than as substitutes for econometric inference. Within the adopted validation framework, K-nearest neighbors achieves the strongest predictive performance. Additional stability checks and local additive explanations improve transparency regarding model tuning and prediction behavior, while confirming that machine-learning outputs should be interpreted as predictive rather than causal evidence. Overall, the findings support integrated and region-sensitive policy approaches combining air-quality management, infrastructure resilience, energy transition, climate adaptation, and public-health planning. Full article

The present research, using finite element method simulation, studies the heat dissipation of a fin-type passive cooling system installed on monocrystalline photovoltaic panels under different environmental conditions associated with altitude. For this purpose, three scenarios at different altitudes were analyzed: Manta (14 m.a.s.l.), Puyo (926 m.a.s.l.), and Ambato (2724 m.a.s.l.). A model simulated using the finite element method, validated in a previous investigation, was used to simulate these three cases. The model was meshed, and the boundary conditions used were obtained from meteorological data averaged over one year. The variables used in this stage were irradiance, ambient temperature, and wind speed in the time range from 08:00 to 17:00. The numerical model used in the simulation considered the mechanisms of conduction in the panel layers, mixed convection toward the surrounding air, and thermal radiation from the exposed surfaces. The results show that, in the city of Ambato, the heat sink presents its best thermal performance. Under conditions of minimum ambient temperature and solar irradiance, a maximum percentage reduction of 3.11% in the photovoltaic panel temperature was obtained, while under conditions of maximum ambient temperature and solar irradiance, the reduction reached 11.11%. This reveals that, when higher panel temperatures occur, the heat sink exhibits better performance. In general, the results showed a reduction in temperature when this heat dissipation mechanism was used. It is evident that the effectiveness of these systems depends not only on geometry or materials, but also on the atmospheric conditions associated with altitude. It is concluded that the heat dissipation capacity of passive cooling mechanisms is influenced by the meteorological conditions of the area, such as ambient temperature, solar irradiance, and wind speed, which may vary according to the altitude at which the system is located. Full article