Search Results (3,716)

Climate change and socio-economic transformation increasingly challenge the stability of China’s food supply. This study aims to optimize grain crop layouts by integrating natural suitability and nutritional supply within a unified analytical framework. Using the MaxEnt model incorporating bioclimatic, topographic, and soil variables, we simulated the natural suitability of major grain crops and compared it with actual planting patterns based on the SPAM dataset. Results revealed substantial spatial discrepancies between actual and suitable distributions, with national planting diversity index increasing by 26.42% (from 0.53 to 0.67) under suitable conditions. Wheat and maize are most suited to northern China, rice and tuber crops to southern regions, while soybean performs optimally in the northeast. Nutrient supply potential also improved substantially under the suitable scenario, with energy, protein, fat, and carbohydrate increasing by 56.9 × 10⁸ KJ, 77.2 × 10⁶ g, 23.3 × 10⁶ g, and 48.6 × 10⁶ g per million people, respectively. Among alternative structures, maize-soybean and maize-based planting structures better aligned with both natural adaptability and nutritional balance (e.g., in Inner Mongolia and Heilongjiang), whereas rice-based structure showed weaker correspondence (e.g., in Shanghai). These findings demonstrate that naturally adaptive optimization can enhance both environmental compatibility and nutritional adequacy, providing scientific guidance for developing climate-resilient and nutrition-oriented crop layout strategies in China. Full article

As an irreplaceable optical ceramic material in energy, aviation, and commerce, sapphire is making a further expansion of its application boundaries. Owing to the anisotropy of sapphire, the material properties analysis in the fabrication process is hard but essential. Hence, aiming at investigating the damage behavior of sapphire with different crystal orientations during machining, the nucleation and propagation of cracks in the orthogonal a, c, and m orientations of sapphire under Vickers indentation were explored experimentally and numerically. Firstly, the indentation morphology and indentation cracks of sapphire with different crystal orientations under different loads were studied based on a Vickers indentation tester. In general, the relative errors of the three characteristic parameters, including the half-length of indentation diagonal, the length of crack, and the maximum depth of indentation, are all within 20% between the simulation model and the indentation test results. Then, the nucleation critical loads of different cracks in sapphire under Vickers indentation are determined on the basis of the ceramic materials’ fracture mechanics theory. The critical load value of the median crack of sapphire in both A- and M-planes is less than 0.1 kgf experimentally and simulatively, while C-plane sapphire is between 1 kgf and 2 kgf. Finally, the stress field, displacement–load curve, plastic piling-up height, and dynamic propagation process during Vickers indentation are analyzed, combining the experimental results with a numerical calculation approach. Full article

Transport is among the fastest-growing contributors to carbon dioxide (CO₂) emissions in the Gulf Cooperation Council (GCC) region, where rapid urbanization, population growth, and high mobility demand continue to shape energy use. This study aims to quantify the extent to which economic growth and urbanization drive transport-related CO₂ emissions across Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates between 2012 and 2022. Using sector-specific data from the International Energy Agency and World Bank, we apply panel and country-level log–log regression models to estimate long-run and short-run elasticities of transport CO₂ emissions with respect to GDP and urban population. The analysis also includes robustness checks excluding the COVID-19 pandemic year to isolate structural effects from temporary shocks. Results show that transport emissions remain strongly correlated with GDP in most countries, indicating emissions-intensive growth, while the influence of urbanization varies: positive in Kuwait and Saudi Arabia, where expansion is car-dependent, and negative in Oman and Qatar, where compact urban forms and transit investments mitigate emissions. The findings highlight the importance of differentiated policy responses—fuel-pricing reform, vehicle efficiency standards, electrification, and transit-oriented planning—to advance low-carbon mobility. By integrating elasticity-based diagnostics with decoupling analysis, this study provides the first harmonized empirical framework for the GCC to assess progress toward transport-sector decarbonization. Full article

Amid mounting calls for socio-ecological transition, many social sciences studies have been exploring the processes of societal change. The well-known Science Technology Society studies (STS) approach focuses on the diffusion of innovation niches as an open-ended process ultimately leading to the stabilization of a new regime. Other works have suggested reversing the perspective, i.e., ‘thinking about transitions from the end’. This is a defining characteristic of system building perspectives, which are inherently goal- and sustainability-oriented. This paper presents the state of the art in the social sciences based on a review of international academic journals in English. We use both quantitative and qualitative approaches. Using Web of Science data collected for a period of ten years and the free software IRaMuTeQ (version 2), we have conducted statistical, similarity, and textual analyses of a corpus of 151 texts, following the PRISMA methodology. We discuss the findings of the lexicometric analysis by looking at the content of the article abstracts. While system building is not always mentioned as such, this new perspective is reflected in the literature, especially in research on the energy and food transition, in two main ways: (i) the procedural and substantive dimensions of sustainability transition are both taken into account; (ii) the issue of governance occupies a central place—involving the definition of appropriate instrument mixes and policy mixes—given the need to deal with stakeholders with diverging interests and values rather than only focusing on technological innovations. Full article

This paper provides a comprehensive analysis of the development, implementation, and evolution of the circular economy indicator (CEI) in the context of hydroelectric turbine refurbishment over the past five decades. By systematically examining publications indexed in the Web of Science database between 1975 and 2025, the study traces the conceptual origins of the CEI, highlights methodological advances, and analyzes practical applications. The analysis focuses on key aspects such as material circularity, energy efficiency, including the share of renewable sources, and the extension of operational lifetime achieved through refurbishment. The paper also identifies persistent methodological gaps, in particular regarding the integration of social and governance dimensions, as well as the lack of standardization across projects, proposing strategies to increase the reliability and applicability of the indicator. The results provide guidance for integrating circular economy principles into hydroelectric refurbishment processes, outline good practices, and set priorities for future research oriented towards more holistic and multidimensional assessments of circularity. Full article

Countries encounter significant challenges in the context of the climate crisis, prompting the implementation of environmentally sustainable measures in vulnerable sectors such as tourism. Nevertheless, inadequate levels of public awareness often delay or—in certain cases—hinder the adoption of such measures. This study focuses on the tourism sector in Greece, which is particularly resource-intensive in terms of energy and water consumption, especially in regions frequently affected by extreme weather events. The study’s objective is to evaluate the level of environmental awareness and behavioral profiles of tourists. Firstly, our study provides a literature review addressing the tourism vulnerabilities related to climate change, the nexus between tourism and environmental pressures, the role of public awareness in shaping policy obstacles, and finally issues related to environmental social and individual responsibility and attitudes. Subsequently, a relevant survey was conducted using a structured questionnaire to outline the profile and preferences of home domestic tourists in Greece. Our results indicate a generally moderate to low level of awareness: approximately 80% of respondents believe tourism has minimal or no impact on climate change, while only about 15% endorsed the need for stricter regulatory measures. Moreover, our findings underscore a significant knowledge gap regarding ongoing challenges related to water resource management. Notably, respondents with higher levels of awareness exhibited more positive attitudes towards sustainability-oriented measures. Overall, our study indicates that enhancing environmental awareness through targeted campaigns and effective communication strategies is crucial. In this respect, cultivating the notion of the “responsible tourist” emerges as a key prerequisite for ensuring the long-term sustainability of the tourism sector in Greece, as a responsible tourist contributes to the long-term sustainability and the tourist profile of a destination for both visitors and residents. Full article

The early stage of architectural design plays a decisive role in determining building energy performance, yet conventional evaluation is typically deferred to later phases, restricting timely and data-informed feedback. This paper proposes EnergAI, a generative design framework that incorporates energy optimization objectives directly into the scheme generation process through large language models (e.g., GPT-4o, DeepSeek-V3.1-Think, Qwen-Max, and Gemini-2.5 pro). A dedicated dataset, LowEnergy-FormNet, comprising 2160 cases with site parameters, massing descriptors, and simulation outputs, was constructed to model site, form, and energy relationships. The framework encodes building massing into a parametric vector representation and employs hierarchical prompt strategies to establish a closed-loop compatibility with ClimateStudio. Experimental evaluations demonstrate that geometry-oriented and fuzzy-goal prompts achieve average annual reductions of approximately 16–17% in energy use intensity and 3–4% in energy cost compared with human designs, while performance-oriented structured prompts deliver the most reliable improvements, eliminating high-energy outliers and yielding an average EUI-saving rate above 50%. In cross-model comparisons under an identical toolchain, GPT-4o delivered the strongest and most stable optimization, achieving 63.3% mean EUI savings, nearly 13% higher than DeepSeek-V3.1-Think, Qwen-Max, and Gemini-2.5 baselines. These results demonstrate the feasibility and indicate the potential robustness of embedding performance constraints at the generation stage, providing a feasible approach to support proactive, data-informed early design. Full article

This paper introduces a control-oriented Linear Parameter Varying (LPV) model of an energy-efficient electric vehicle, enhanced to account for wind-induced disturbances. The proposed model structure is designed to support model-based control strategies focused on minimizing energy consumption. In addition to core control inputs—such as torque reference and cornering radius—the model integrates a simulated representation of wind effects on the vehicle’s longitudinal dynamics. To manage the underlying nonlinearities of the vehicle dynamics, a trajectory-based linearization approach was employed to construct the baseline LPV model without wind effects. The accuracy of the extended model was validated using real-world speed profile data. Owing to its modular and control-compatible design, the model provides a solid foundation for testing and developing energy-saving control strategies, making it especially applicable to the design and operation of energy-efficient electric vehicles. The proposed model holds significant potential for further reducing energy consumption, particularly in urban transportation scenarios. Full article

Hot dry rock (HDR) is a promising renewable energy resource whose vast reserves and wide distribution have attracted extensive attention in recent years. However, exploiting HDR resources requires hydraulic stimulation, which is typically accompanied by substantial microseismic activity, posing significant risks to project safety and public acceptance. Current understanding of microseismic mechanisms, particularly the role of fracture geometry under varying injection schemes, remains inadequate. This study employs a three-dimensional block-based discrete element method to construct a fluid–mechanics coupled model founded on a discrete fracture network, aimed at investigating the mechanical behavior of fractures and the spatial distribution of microseismicity during hydraulic stimulation. Our results quantitatively demonstrate that fractures oriented at 45° to the maximum principal stress are most susceptible to shear reactivation and microseismic clustering, with event magnitudes strongly correlated to both fracture orientation and intra-fracture fluid pressure. Consequently, preventing critically high fluid pressures in natural fractures near the injection well, particularly those at approximately 45° to the maximum principal stress direction, is essential for risk mitigation. Cyclic injection can shear more fractures and slightly reduce magnitudes via staged pressure relaxation, but its effectiveness in controlling microseismic magnitude is limited. Therefore, it is recommended to implement measures to control the entry of fracturing fluid into these high-risk fissures, such as segmented fracturing or temporary plugging techniques. This strategy is expected to enhance seismic risk mitigation, thereby contributing to the safe and efficient exploitation of deep geothermal resources. Full article

Explosive welding technology is crucial for the production of large-area plates composed of materials with varying plastic and physical properties. Severe plastic deformation processes increase the mechanical strength of the plates by refining grains and increasing dislocation density. The aim of the research presented in this paper was to analyze the effect of Equal Channel Angular Pressing (ECAP) on the mechanical properties and microstructure of an Al/Cu (EN AW-1050/Cu-ETP) bimetallic plate produced by the explosive welding technology. The ECAP process was carried out at room temperature. The ECAP experiments consisted of 1–3 passes using a die with a channel angle of 90°. The ram speed was 40 mm/min. The study also considered various sample cutting orientations (longitudinal, transverse) and various positions of the bimetallic sample in the die entry channel. Rotating the sample by an angle of 180° between consecutive passes was also considered. To achieve the research objective, static tensile tests, Vickers hardness tests at a load of 4.9 N, and microstructural analysis of the samples using scanning electron microscopy and energy dispersive spectroscopy were carried out. It was found that each subsequent pass in the ECAP process led to a gradual, severe change in the morphology of the Al/Cu interfacial transition layer. The orientation of the cutting plane of the samples was shown to have no effect on the hardness of the bimetallic material. Vickers hardness tests preceded by the ECAP process revealed a more uniform hardness distribution compared to the base material. The orientation of the Al/Cu plate layers in the ECAP die channel clearly influenced the character of the hardness distribution. Full article

Integrated energy systems (IES) are central to sustainable energy transitions because sector coupling can raise renewable utilization and cut greenhouse gas emissions. Yet, traditional optimizers often become trapped in local optima and struggle with multi-objective trade-offs between economic and environmental goals. This study applies the hippopotamus optimization algorithm (HOA) to the sustainability-oriented, multi-objective operation of an electricity–gas–heat IES that incorporates power-to-gas (P2G), photovoltaic generation, and wind power. We jointly minimize operating cost and carbon emissions while improving renewable energy utilization. In comparative tests against pigeon-inspired optimization (PIO) and particle swarm optimization (PSO), HOA achieves superior Pareto performance, lowering operating costs by ~1.5%, increasing energy utilization by 16.3%, and reducing greenhouse gas emissions by 23%. These gains stem from HOA’s stronger exploration–exploitation balance and the flexibility introduced by P2G, which converts surplus electricity into storable gas to support heat and power demands. The results confirm that HOA provides an effective decision tool for sustainable IES operation, enabling deeper variable-renewable integration, lower system-wide emissions, and improved economic outcomes, thereby offering practical guidance for utilities and planners pursuing cost-effective decarbonization. Full article

This study investigates the thermal resilience of naturally ventilated Lebanese residential buildings in the context of future climates, based on four climate zones: coastal (moderate and humid), low mountain (cool and seasonally variable), inland plateau (semi-arid with high summer heat), and high mountain (cold, with significant winter conditions). The aim of the study is to evaluate how passive envelope interventions can enhance indoor thermal resilience under five present and future work scenarios: TMY, SSP1-2.6 (2050 and 2080), and SSP5-8.5 (2050 and 2080). A baseline model was developed for typical building stock in each climate using EnergyPlus-23.2.0. The passive design parameters of window type, shading depth, and building orientation were systematically altered to analyze their effect on thermal comfort and building thermal resilience. Unlike previous studies that assessed either individual passive strategies or a single climate condition, this research combines multi-objective optimizations with overheating resilience metrics, by optimizing passive interventions using the GenOpt-3.1.0 and BESOS (Python-3.7.3 packages to minimize indoor overheating degree (IOD) and maximize climate change overheating resistivity (CCOR) index. Our findings indicate that optimized passive interventions, such as deep shading (0.6–1.0 m), low-e or bronze glazing, and southern orientations, can reduce overheating in all climate zones, reflecting a substantial improvement in thermal resilience. The novelty of this work lies in combining passive envelope optimization with future climate situations and a long-term overheating resilience index (CCOR) in the Mediterranean region. The results provide actionable suggestions for enhancing buildings’ resilience to climate change in Lebanon, thus informing sustainable design practice within the Eastern Mediterranean climate. Full article

Amid the combined pressures of global carbon-reduction in architecture and the imperative of cultural heritage conservation, new courtyard-style buildings in hot-summer and cold-winter regions face a dual challenge of reconciling historical morphological constraints with contemporary comfort requirements. At the same time, the prevailing energy-efficiency codes in these regions, emphasizing high airtightness and strong insulation, have revealed shortcomings such as poor indoor air quality and insufficient summer ventilation. This study takes the Lu Residence in Dongyang, Jinhua, Zhejiang Province, as the primary case. It systematically examines the coupling mechanisms between the geometric configurations of transitional space in traditional courtyard dwellings and their environmental physical parameters using field surveys, multi-parameter environmental monitoring, and computer simulations. The results identify the optimal orientations and geometric parameters that balance summer ventilation with winter thermal buffering in hot-summer and cold-winter regions. The primary conclusions of this research are as follows: (1) The optimal orientation for axial buildings lies between 15° west of south and 15° east of south, as well as 30–60° east or west of south, with an angle of 45–60° in relation to the prevailing annual wind direction for all buildings. (2) The optimal height-to-width ratio of the courtyard is less than 1:2.5, while the range of the length-to-width ratio extends from 1:0.5 to 1:0.7. (3) The optimal eave depth varies from 900 to 1500 mm, effectively balancing winter heat retention and summer shading; however, a depth of 2400 mm is primarily advantageous for shading purposes. Furthermore, these findings are applied to the design of a new guesthouse within the conservation area of the Xu Zhen Er Gong Ancestral Hall in Yongkang, establishing a climate–geometry matching mechanism for transitional spaces. The study demonstrates that transitional space can serve as effective passive regulators, offering a scientific and sustainable pathway for the adaptive continuation of traditional courtyard architecture. Full article

Geological models form the basis for scientific investigations of both the surface and subsurface of urban environments. Urban cover, however, usually prohibits the collection of new subsurface data. Therefore, models depend on existing subsurface datasets that are often of poor quality and have an uneven spatial and temporal distribution, introducing significant uncertainty. This research proposes a novel method to mitigate uncertainty caused by clusters of uncertain data points in kriging-based geological modelling. This method estimates orientations from clusters of uncertain data and randomly selects points for geological interpolation. Unlike other approaches, it relies on the spatial distribution of the data and translating geological information from points to geological orientations. This research also compares the proposed approach to locally changing the accuracy of the interpolator through data-informed local smoothing. Using the Ouseburn catchment, Newcastle upon Tyne, UK, as a case study, results indicate good correlation between both approaches and known conditions, as well as improved performance of the proposed methodology in model validation. Findings highlight a trade-off between model uncertainty and model precision when using highly uncertain datasets. As urban planning, water resources, and energy analyses rely on a robust geological interpretation, the modelling objective ultimately guides the best modelling approach. Full article

This study presents a systematic bibliographic review of the application of Big Data and machine learning (ML) methods to improve energy efficiency in architectural design. The review covers peer-reviewed publications from 2010 to 2025, examining how ML algorithms such as Random Forest, Gradient Boosting, and neural networks have been used to optimise design parameters including orientation, glazing ratio, and compactness. A systematic search and selection protocol was applied to identify, classify, and critically analyse over 70 relevant studies. The findings reveal consistent evidence that data-driven models outperform traditional simulation-based methods in predicting heating and cooling loads while highlighting current gaps related to data quality, model interpretability, and real-world validation. The study contributes to the understanding of how ML-driven approaches can guide sustainable architectural design and future research directions in the built environment. Additionally, illustrative experiments were performed using simulated datasets to validate and exemplify key findings identified in the reviewed studies. Full article