Search Results (167)

Building performance simulation is crucial for the design and optimization of sustainable buildings. However, the increasing complexity of building systems necessitates advanced modeling techniques capable of handling multi-domain interactions. This paper presents a novel application of the bond graph (BG) methodology to simulate and analyze the thermal behavior of an integrated trigeneration system within an experimental test cell. Unlike conventional simulation approaches, the BG framework enables unified modeling of thermal and hydraulic subsystems, offering a physically consistent and energy-based representation of system dynamics. The study investigates the system’s performance under both dynamic and steady-state conditions across two distinct climatic periods. Validation against experimental data reveals strong agreement between measured and simulated temperatures in heating and cooling scenarios, with minimal deviations. This confirms the method’s reliability and its capacity to capture transient thermal behaviors. The results also demonstrate the BG model’s effectiveness in supporting predictive control strategies, optimizing energy efficiency, and maintaining thermal comfort. By integrating hydraulic circuits and thermal exchange processes within a single modeling framework, this work highlights the potential of bond graphs as a robust and scalable tool for advanced building performance simulation. Full article

Understanding how energy use and economic activity shape carbon emissions is pivotal for achieving global climate targets. This study quantifies the dynamic nexus between disaggregated energy consumption, economic growth, and CO₂ emissions in India and China—two economies that together account for more than one-third of global emissions. Using annual data from 1990 to 2021, we implement Long Short-Term Memory (LSTM) neural networks, which outperform traditional linear models in capturing nonlinearities and lagged effects. The dataset is split into training (1990–2013) and testing (2014–2021) intervals to ensure rigorous out-of-sample validation. Results reveal stark national differences. For India, coal, natural gas consumption, and economic growth are the strongest positive drivers of emissions, whereas renewable energy exerts a significant mitigating effect, and nuclear energy is negligible. In China, emissions are dominated by coal and petroleum use and by economic growth, while renewable and nuclear sources show weak, inconsistent impacts. We recommend retrofitting India’s coal- and gas-plants with carbon capture and storage, doubling clean-tech subsidies, and tripling annual solar-plus-storage auctions to displace fossil baseload. For China, priorities include ultra-supercritical upgrades with carbon capture, utilisation, and storage, green-bond-financed solar–wind buildouts, grid-scale storage deployments, and hydrogen-electric freight corridors. These data-driven pathways simultaneously cut flagship emitters, decouple GDP from carbon, provide replicable models for global net-zero research, and advance climate-resilient economic growth worldwide. Full article

With the rapid increase in traffic volume and the number of heavy-duty vehicles, the load on asphalt pavements has increased significantly. Especially on sections with long longitudinal slopes, the internal stress conditions of asphalt pavement have become even more complex. This study aims to investigate the thermal–mechanical coupling behavior of asphalt pavement structures on long longitudinal slopes under the combined influence of temperature fields and moving loads. A pavement temperature field model was developed based on the climatic conditions of Nanning (AAT: 21.8 °C; Tmax: 37 °C; Tmin: 3 °C; AAP: 1453.4 mm). In addition, a three-dimensional finite element model of asphalt pavement structures on long longitudinal slopes was established using finite element software. Variations in pavement mechanical responses were compared under different vehicle axle loads (100–200 kN), slope gradients (0–5%), braking coefficients (0–0.7), and asphalt mixture layer thicknesses (2–8 cm). The results indicate that the pavement structure exhibits a strong capacity for pressure attenuation, with the middle and lower surface layers showing more pronounced stress reduction—up to 40%—significantly greater than the 6.5% observed in the upper surface layer. As the axle load increases from 100 kN to 200 kN, the internal mechanical responses of the pavement show a linear relationship with load magnitude, with an average increase of approximately 29%. In addition, the internal shearing stress of the pavement is more sensitive to changes in slope and braking coefficient; when the slope increases from 0% to 5% and the braking coefficient increases from 0 to 0.7, the shear stress at the bottom of the upper surface layer increases by 12% and 268%, respectively. This study provides guidance for the design of asphalt pavements on long longitudinal slopes. In future designs, special attention should be given to enhancing the shear strength of the surface layer and improving the interlayer bonding performance. In particular, under conditions of steep slopes and frequent heavy vehicle traffic, the thickness and modulus of the upper surface asphalt mixture may be appropriately increased. Full article

Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article

This study explores the interplay of climate vulnerability and social capital in two rural communities: Brajaballavpur, a high-climate-prone village in the Indian Sundarbans characterized by high ecological fragility, recurrent cyclones, and saline water intrusion affecting water access, livelihoods, and infrastructure; and Jemua, a low-climate-prone village in the land-locked district of Paschim Bardhaman, West Bengal, India, with no extreme climate events. A total of 85 participants (44 in Brajaballavpur, 41 in Jemua) were selected through purposive sampling. Using a comparative qualitative research design grounded in ethnographic fieldwork, data were collected through household interviews, Participatory Rural Appraisals (PRAs), Focus Group Discussions (FGDs), and Key Informant Interviews (KIIs), and analyzed manually using inductive thematic analysis. Findings reveal that bonding and bridging social capital were more prominent in Brajaballavpur, where dense horizontal ties supported collective action during extreme weather events. Conversely, linking social capital was more visible in Jemua, where participants more frequently accessed formal institutions such as the Gram Panchayat, local NGOs, and government functionaries that facilitated grievance redressal and information access, but these networks were concentrated among more politically connected individuals. The study concludes that climate vulnerability shapes the type, strength, and strategic use of social capital in village communities. While bonding and bridging ties are crucial in high-risk contexts, linking capital plays a critical role in enabling long-term social structures in lower-risk settings. The study contributes to both academic literature and policy design by offering a relational and place-based understanding of climate vulnerability and social capital. Full article

Redox signaling is central to plant adaptation, influencing metabolic regulation, stress responses, and developmental processes through thiol-based oxidative post-translational modifications (oxiPTMs) of redox-sensitive proteins. These modifications, particularly those involving cysteine (Cys) residues, act as molecular switches that alter protein function, structure, and interactions. Advances in mass spectrometry-based redox proteomics have greatly enhanced the identification and quantification of oxiPTMs, enabling a more refined understanding of redox dynamics in plant cells. In parallel, the emergence of computational modeling, artificial intelligence (AI), and machine learning (ML) has revolutionized the ability to predict redox-sensitive residues and characterize redox-dependent signaling networks. This review provides a comprehensive synthesis of methodological advancements in redox proteomics, including enrichment strategies, quantification techniques, and real-time redox sensing technologies. It also explores the integration of computational tools for predicting S-nitrosation, sulfenylation, S-glutathionylation, persulfidation, and disulfide bond formation, highlighting key models such as CysQuant, BiGRUD-SA, DLF-Sul, and Plant PTM Viewer. Furthermore, the functional significance of redox modifications is examined in plant development, seed germination, fruit ripening, and pathogen responses. By bridging experimental proteomics with AI-driven prediction platforms, this review underscores the future potential of integrated redox systems biology and emphasizes the importance of validating computational predictions, through experimental proteomics, for enhancing crop resilience, metabolic efficiency, and precision agriculture under climate variability. Full article

This study focuses on the influence of prolonged ultraviolet (UV) irradiation on the mechanical properties and surface microstructure of glass fiber-reinforced plastics (GFRPs) and basalt fiber-reinforced plastics (BFRPs), which are widely used in construction and transport infrastructure. The relevance of the research lies in the need to improve the reliability of composite materials under extended exposure to harsh climatic conditions. Experimental tests were conducted in a laboratory UV chamber over 2000 h, simulating accelerated weathering. Mechanical properties were evaluated using three-point bending, while surface conditions were assessed via profilometry and microscopy. It was shown that GFRPs exhibit a significant reduction in flexural strength—down to 59–64% of their original value—accompanied by increased surface roughness and microdefect depth. The degradation mechanism of GFRPs is attributed to the photochemical breakdown of the polymer matrix, involving free radical generation, bond scission, and oxidative processes. To verify these mechanisms, FTIR spectroscopy was employed, which enabled the identification of structural changes in the polymer phase and the detection of mass loss associated with matrix decomposition. In contrast, BFRP retained up to 95% of their initial strength, demonstrating high resistance to UV-induced aging. This is attributed to the shielding effect of basalt fibers and their ability to retain moisture in microcavities, which slows the progress of photo-destructive processes. Comparison with results from natural exposure tests under extreme climatic conditions (Yakutsk) confirmed the reliability of the accelerated aging model used in the laboratory. Full article

Freeze–thaw damage is a critical durability challenge in cold climates that leads to surface spalling, cracking, and degradation of structural performance. In northern China, the severity of winter conditions further accelerates the degradation of concrete infrastructure. This study investigates the reinforcement of frost-damaged concrete using engineered cementitious composites (ECC) prepared with Yellow River sedimentary sand (YRS), employed as a 100% mass replacement for quartz sand to promote sustainability. The interface bonding performance of ECC-C40 specimens was evaluated by testing the impact of various surface roughness treatments, freeze–thaw cycles, and interface agents. A multi-factor predictive formula for determining interface bonding strength was created, and the bonding mechanism and model were examined through microscopic analysis. The results show that ECC made with YRS significantly improved the interface bonding performance of ECC-C40 specimens. Specimens treated with a cement expansion slurry as the interface agent and those subjected to the splitting method for surface roughness achieves the optimal reinforced condition, exhibited a 27.57%, 35.17%, 43.57%, and 42.92% increase in bonding strength compared to untreated specimens under 0, 50, 100, and 150 cycles, respectively. Microscopic analysis revealed a denser interfacial microstructure. Without an interface agent, the bond interface followed a dual-layer, three-zone model; with the interface agent, a three-layer, three-zone model was observed. Full article

Under the global initiative for automotive lightweighting to address climate challenges, this study investigates the microstructure evolution of steel–aluminum composites processed by hot equal-channel angular pressing (H-ECAP). Using 6061-T6 aluminum cores clad with 20 # low carbon steel tubes processed through 1–4 C-path passes (Φ = 120°, ψ = 30°), we demonstrate significant microstructural improvements. The steel component showed progressive grain refinement from 2.2 μm (1 pass) to 1.3 μm (4 pass), with substructures decreasing from 72.19% to 35.46%, HAGB increasing from 31.2% to 34.6%, and hardness increasing from 222 HV to 271 HV. Concurrently, aluminum experienced grain refinement from 59.3 μm to 28.2 μm, with recrystallized structures surging from 0.97% to 71.81%, HAGB increasing from 9.96% to 63.76%, and hardness increasing from 51.4 HV to 83.6 HV. The interfacial layer thickness reduced by 74% (29.98 μm to 7.78 μm) with decreasing oxygen content, containing FeAl₃, Fe₂Al₅, and minimal matrix oxides. Yield strength gradually increased from 361 MPa (one pass) to 372.35 MPa (four passes), accompanied by a significant enhancement in compressive strength. These findings reveal that H-ECAP’s thermomechanical coupling effect effectively enhances interface bonding quality while suppressing detrimental intermetallic growth, providing a viable solution to overcome traditional manufacturing limitations in steel–aluminum composite applications for sustainable mobility. Full article

At a time of climate change, farmers face difficulties in providing food for a growing population. This results in the overuse of water and fertilisers. The aim of the research was to test the possibility of introducing waste sheep wool fibres into a hydrogel to obtain a stable material that could improve water retention and could serve as a fertiliser material matrix. Wool fibres and hydrogel were chosen because of their ability to store water and their degradability. An evaluation of the swelling degree of different alginate-based hydrogel matrices was performed to select the matrix. The stability and water bonding of hydrogels with different wool fibre content were analysed and evaluated by thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The microstructure and the effect of fibres on the uniformity of the hydrogel were assessed using SEM and optical microscopy. The degree of water retention in the soil was also evaluated. The results showed that it is possible to incorporate wool fibres into the hydrogel matrix and the wool fibres make the composite porous, which allows water penetration into the material much more easily. This research has shown the possibility of using waste wool fibres as an active ingredient in sustainable fertiliser materials. Full article

Under the background of climate change, the risk spillover within the energy system is constantly intensifying. Clarifying the coupling relationship between entities within the energy system can help policymakers propose more reasonable policy measures and strengthen risk prevention. To estimate the risk spillover of energy-related systems, this paper constructs five subsystems: the fossil fuel subsystem, the electricity subsystem, the green bond subsystem, the renewable energy subsystem, and the carbon subsystem. Then, a quantitative risk analysis is conducted on two major energy consumption/carbon emission entities, China and Europe, based on the DCC-GARCH-CoVaR method. The result shows that (1) Markets of the same type often have more significant dynamic correlations. Of these, the average dynamic correlation coefficient of GBI-CABI (the Chinese green bond subsystem) and FR-DE (the European electricity subsystem) are the largest, by 0.8552 and 0.7347. (2) The high correlation between energy markets results in serious risk contagion, and the overall risk spillover effect within the European energy system is about 2.6 times that within the Chinese energy system. Of these, EUA and CABI are the main risk connectors of each energy system. Full article

An asphalt modifier dry-process direct-cast oil-rich high-viscosity high-elasticity (OR-HV-HE) was developed to address the climatic characteristics of seasonal freezing zones. The chemical composition of the OR-HV-HE modifier was optimized through orthogonal testing. Advanced characterization techniques, including thermogravimetric analysis (TG), differential scanning calorimetry (DSC), scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR), were employed to systematically analyze the comprehensive thermal properties, microstructure, and chemical characteristics of the OR-HV-HE asphalt. Test results revealed a linear inverse relationship between the melt index and the OR-HV-HE asphalt grafting rate. The addition of the OR-HV-HE modifier led to the generation of new chemical bonds, and microscopic mechanism analysis illustrated the formation of a cross-linking network structure between the OR-HV-HE and asphalt, in which the cross-linking network structure could enhance the high and low-temperature performance of asphalt. Road performance verification results demonstrated that when compared with the traditional SBS-modified asphalt mixture, the OR-HV-HE modified asphalt mixture exhibited significantly superior road performance indices: the high-temperature dynamic stability was increased by 468% and the low-temperature damage strain was increased by 47.5%, and the residual stability reached 99%. Full article

This study investigates the influence of exposure to climate change on the readability of narrative disclosures in annual reports. Analyzing a sample of 38,229 firm-year observations from 2002 to 2022, the study provides evidence supporting the information obfuscation hypothesis. Specifically, it finds that exposure to climate change is linked to less readable annual reports. This effect is both statistically and economically significant; a one standard deviation increase in climate change exposure leads to an 8.5% reduction in readability. Moreover, this effect is particularly evident among firms operating in environmentally sensitive industries, as well as those characterized by weak corporate culture. Additional tests indicate that the different aspects of climate change exposure (opportunity, physical, and regulatory) are individually associated with a decrease in readability of annual reports, with the physical dimension exerting the most significant impact. The findings underscore the necessity of implementing measures to mitigate climate change exposure and enhance sustainable business environments, such as transitioning to renewable energy sources (such as solar, wind, and hydro), minimizing dependence on fossil fuels, minimizing emissions from industries and transportation, sourcing low-carbon materials, adopting circular economy models, directing capital toward climate-friendly projects, and managing climate risks through catastrophe bonds and climate insurance. The significance of these actions is underscored by the impact of climate change on firms’ information environments, as documented in the current study. Full article

As global climate change intensifies and carbon emission policies become increasingly stringent, carbon risk has emerged as a crucial factor influencing corporate operations and financial markets. Based on data from A-share listed companies in China from 2009 to 2022, this paper empirically examines the pricing mechanism of carbon risk in the Chinese capital market and explores how different corporate signaling behaviors affect the carbon risk premium. The findings reveal the following: (1) Carbon risk exhibits a significant positive premium (annualized at about 1.33% per standard deviation), which remains robust over longer time windows and after replacing the measurement variables. (2) Heterogeneity analysis shows that the carbon risk premium is not significant in high-energy-consuming industries or before the signing of the Paris Agreement, possibly due to changes in investor expectations and increased green awareness. Additionally, a significant difference in the carbon risk premium exists between brown and green stocks, reflecting a “labeling effect” of green attributes. (3) Issuing green bonds, as an active corporate signaling behavior, effectively mitigates the carbon risk premium, indicating that market investors highly recognize and favor firms that actively convey green signals. (4) A “greenwashing” indicator constructed from textual analysis of environmental information disclosure suggests that greenwashing leads to a mispricing of the carbon risk premium. Companies that issue false green signals—publicly committing to environmental protection but failing to implement corresponding emission reduction measures—may mislead investors and create adverse selection problems. Finally, this paper provides recommendations for corporate carbon risk management and policy formulation, offering insights for both research and practice in the field. Full article

Extreme climatic conditions characterized by drastic temperature fluctuations exacerbate soil erosion through intensified thermo-mechanical weathering processes. Loess-covered regions are particularly vulnerable to such conditions because of the inherent thermo-sensitivity of loess. A comprehensive investigation of mechanisms of thermo-mechanical weathering in loess under extreme temperature regimes holds critical importance for elucidating soil degradation patterns. It is also essential for formulating mitigation strategies in climate-sensitive loess terrains, especially given the increasing frequency of extreme weather events under global warming scenarios. This study employed integrated physical monitoring experiments and numerical modeling. The evolutionary patterns of temperature fields and corresponding thermal stress distributions in loess subjected to both heat shock (rapid heating) and cold shock (rapid cooling) conditions were systematically examined. The key findings are as follows: (1) Soil temperature variations demonstrate phase-lagged responses to ambient thermal variations during both shock scenarios, exhibiting distinct thermal inertia effects. (2) The spatial distribution pattern of thermal stress is predominantly governed by the temperature gradient within the soil matrix. (3) While the magnitude ranges of thermal stress remain comparable between shock types, their directional characteristics fundamentally differ; heat shocks induce surface compressive stresses and internal tensile stresses, whereas cold shocks generate inverse stress patterns. (4) Compared to heat shock, cold shocks trigger obvious surface degradation through tensile stress-induced failure of particle bonds. These mechanically weakened zones establish favorable conditions for subsequent erosion processes in loess landscapes. Full article