Search Results (370)

An in-depth investigation into the evolutionary characteristics, transmission mechanisms, and optimization pathways of electricity consumption linkages across China’s industrial sectors highlights their substantial theoretical and practical significance in achieving the “dual carbon” goals and advancing high-quality economic development. This study investigates the structural characteristics and developmental trends of electricity consumption linkages across China’s industrial sectors using an enhanced hypothetical extraction method. The analysis draws on national input–output tables and sector-specific electricity consumption data during the period from 2002 to 2020. Key transmission routes between industrial sectors are identified through path analysis and average path length calculations. The findings reveal that China’s industrial electricity consumption structure is marked by notable scale expansion and differentiation. The magnitude of inter-sectoral electricity flows continues to grow steadily. The evolution of these linkages exhibits clear phase-specific patterns, while the intensity of electricity consumption connections across sectors shows pronounced heterogeneity. Furthermore, the transmission path analysis revealed differentiated characteristics of electricity influence transmission, with generally shorter internal paths within sectors, significant cross-sectoral transmission differences, and manufacturing demonstrating good transmission accessibility with moderate path distances to major sectors. These insights provide a robust foundation for designing differentiated energy conservation policies, as well as for optimizing the overall structure of industrial electricity consumption. Full article

Amidst global climate change, carbon emissions across the edible vegetable oil supply chain are critical for sustainable development. This paper systematically reviews the existing literature, employing life cycle assessment (LCA) to analyze key factors influencing carbon footprints at stages including cultivation, processing, and transportation. It reveals the differential impacts of fertilizer application, energy structures, and regional policies. Unlike previous reviews that focus on single crops or regions, this study uniquely integrates global data across major edible oils, identifying three critical gaps: methodological inconsistency (60% of studies deviate from the requirements and guidelines for LCA); data imbalance (80% concentrated on soybean/rapeseed); weak policy-technical linkage. Key findings: fertilizer emissions dominate cultivation (40–60% of total footprint), while renewable energy substitution in processing reduces emissions by 35%. Future efforts should prioritize multidisciplinary integration, enhanced data infrastructure, and policy scenario analysis to provide scientific insights for the low-carbon transformation of the global edible oil industry. Full article

The relationship between ecosystem services (ESs) and human well-being (HWB) is a central issue of sustainable development. However, current research often relies on qualitative frameworks or indicator-based assessments, limiting a comprehensive understanding of the relationship between natural environment and human acquisition, which still needs to be strengthened. As an element transferred in the natural–society coupling system, carbon can assist in characterizing the dynamic interactions within coupled human–natural systems. Carbon, as a fundamental element transferred across ecological and social spheres, offers a powerful lens to characterize these linkages. This study develops and applies a novel analytical framework that integrates carbon flow as a unifying metric to quantitatively assess the spatiotemporal dynamics of the land use and land cover change (LUCC)–ESs–HWB nexus in Guizhou Province, China, from 2000 to 2020. The results show that: (1) Ecosystem services in Guizhou showed distinct trends from 2000 to 2020: supporting and regulating services declined and then recovered, and provisioning services steadily increased, while cultural services remained stable but varied across cities. (2) Human well-being generally improved over time, with health remaining stable and the HSI rising across most cities, although security levels fluctuated and remained low in some areas. (3) The contribution of ecosystem services to human well-being peaked in 2010–2015, followed by declines in central and northern regions, while southern and western areas maintained or improved their levels. (4) Supporting and regulating services were positively correlated with HWB security, while cultural services showed mixed effects, with strong synergies between culture and health in cities like Liupanshui and Qiandongnan. Overall, this study quantified the coupled dynamics between ecosystem services and human well-being through a carbon flow framework, which not only offers a unified metric for cross-dimensional analysis but also reduces subjective bias in evaluation. This integrated approach provides critical insights for crafting spatially explicit land management policies in Guizhou and offers a replicable methodology for exploring sustainable development pathways in other ecologically fragile karst regions worldwide. Compared with conventional ecosystem service frameworks, the carbon flow approach provides a process-based, dynamic mediator that quantifies biogeochemical linkages in LUCC–ESs–HWB systems, which is particularly important in fragile karst regions. However, we acknowledge that further empirical comparison with traditional ESs metrics could strengthen the framework’s generalizability. Full article

Understanding the price dynamics of oil futures is crucial for advancing green finance strategies and supporting sustainable energy transitions. This study investigates the macroeconomic and energy market determinants of oil futures prices through Granger causality, cointegration analysis, and the error correction model, using daily data. It focuses on the influence of economic development levels, exchange rate fluctuations, and inter-energy price linkages. The empirical findings indicate that (1) oil futures prices exhibit strong correlations with other energy prices, macroeconomic factors, and exchange rate variables; (2) economic development significantly affects oil futures prices, while exchange rate impacts are statistically insignificant based on the daily data analyzed; (3) there exists a stable long-term equilibrium relationship between oil futures prices and variables representing economic activity, exchange rates, and energy market trends; (4) oil futures prices exhibit significant short-term dynamics while adjusting steadily toward a long-run equilibrium driven by macroeconomic and energy market fundamentals. By enhancing the accuracy of oil futures price forecasting, this study offers practical insights for managing financial risks associated with fossil energy markets and contributes to the formulation of low-carbon investment strategies. The findings provide a valuable reference for integrating energy pricing models into sustainable finance and climate-aligned portfolio decisions. Full article

Unveiling the relationship between the “Water–Carbon–Ecology” (W-C-E) footprints embodied in regional trade and resource flows is crucial for enhancing the synergistic benefits between economic development and environmental protection. This study constructs an association framework based on the Multi-Regional Input–Output (MRIO) model to systematically evaluate the “W-C-E” footprints and resource flow characteristics of the Yangtze River Economic Belt and the Yellow River Basin. By integrating import and export trade data, this study reveals the patterns of resource flows within and outside these regions. This research delineates the connection patterns between the “W-C-E” footprints and resource flows across three dimensions: spatial, sectoral, and environmental–economic factors. The results indicate that the Yangtze River Economic Belt has gained significant economic benefits from regional trade but also bears substantial environmental costs. Import and export trade further exacerbate the imbalance in regional resource flows, with the Yangtze River Economic Belt exporting many embodied resources through high-energy-consuming products, while the Yellow River Basin increases resource input by importing products such as food and tobacco. Sectoral analysis reveals that agriculture, electricity and water supply, and mining are the sectors with the highest net output of “W-C-E” footprints in both regions, whereas services, food and tobacco, and construction are the sectors with the highest net input. The comprehensive framework of this study can be extended to the analysis of resource–environment–economic systems in other regions, providing methodological support for depicting complex human–land system linkage patterns. Full article

This study reported covalent organic frameworks (COFs) and their hybrid composites with two-dimensional materials, graphene oxide (GO), graphitic carbon nitride (g-C₃N₄), and boron nitride (BN), to examine their structural, textural, and gas adsorption properties. Material characterization confirmed the crystallinity of COF-1 and the preservation of framework integrity after integrating the 2D nanomaterials. FT-IR spectra exhibited pronounced vibrational fingerprints of imine linkages and validated the functional groups from the COF and the integrated nanomaterials. TEM images revealed the integration of the two components, porous, layered structures with indications of interfacial interactions between COF and 2D nanosheets. Nitrogen adsorption–desorption isotherms revealed the microporous characteristics of the COFs, with hysteresis loops evident, indicating the development of supplementary mesopores at the interface between COF-1 and the 2D materials. The BET surface area of pristine COF-1 was maximal at 437 m²/g, accompanied by significant micropore and Langmuir surface areas of 348 and 1290 m²/g, respectively, offering enhanced average pore widths and hierarchical porous strcuture. CO₂ adsorption tests were investigated showing maximum adsorption capacitiy of 1.47 mmol/g, for COF-1, closely followed by COF@BN at 1.40 mmol/g, underscoring the preserved sorption capabilities of these materials. These findings demonstrate the promise of designed COF-based hybrids for gas capture, separation, and environmental remediation applications. Full article

Ecological security patterns (ESPs) are fundamental to safeguarding regional ecological integrity and enhancing human well-being. Consequently, research on conservation and restoration in critical regions is vital for ensuring ecological security and optimizing territorial ecological spatial configurations. Focusing on the Henan section of the Yellow River Basin, this study established the regional ESP and conservation–restoration framework through an integrated approach: (1) assessing four key ecosystem services—soil conservation, water retention, carbon sequestration, and habitat quality; (2) identifying ecological sources based on ecosystem service importance classification; (3) calculating a comprehensive resistance surface using the entropy weight method, incorporating key factors (land cover type, NDVI, topographic relief, and slope); (4) delineating ecological corridors and nodes using Linkage Mapper and the minimum cumulative resistance (MCR) theory; and (5) integrating ecological functional zoning to synthesize the final spatial conservation and restoration strategy. Key findings reveal: (1) 20 ecological sources, totaling 8947 km² (20.9% of the study area), and 43 ecological corridors, spanning 778.24 km, were delineated within the basin. Nineteen ecological barriers (predominantly located in farmland, bare land, construction land, and low-coverage grassland) and twenty-one ecological pinch points (primarily clustered in forestland, grassland, water bodies, and wetlands) were identified. Collectively, these elements form the Henan section’s Ecological Security Pattern (ESP), integrating source areas, a corridor network, and key regional nodes for ecological conservation and restoration. (2) Building upon the ESP and the ecological baseline, and informed by ecological functional zoning, we identified a spatial framework for conservation and restoration characterized by “one axis, two cores, and multiple zones”. Tailored conservation and restoration strategies were subsequently proposed. This study provides critical data support for reconciling ecological security and economic development in the Henan Yellow River Basin, offering a scientific foundation and practical guidance for regional territorial spatial ecological restoration planning and implementation. Full article

In the context of the intensifying global climate crisis, the power industry, as a significant carbon emitter, urgently needs to promote low-carbon transformation using market mechanisms. In this paper, a multi-objective stochastic optimization scheduling framework for regional power grids integrating carbon trading (CET) and green certificate trading (GCT) is proposed to coordinate the conflict between economic benefits and environmental objectives. By building a deterministic optimization model, the goal of maximizing power generation profit and minimizing carbon emissions is combined in a weighted form, and the power balance, carbon quota constraint, and the proportion of renewable energy are introduced. To deal with the uncertainty of power demand, carbon baseline, and the green certificate ratio, Monte Carlo simulation was further used to generate random parameter scenarios, and the CPLEX solver was used to optimize scheduling schemes iteratively. The simulation results show that when the proportion of green certificates increases from 0.35 to 0.45, the proportion of renewable energy generation increases by 4%, the output of coal power decreases by 12–15%, and the carbon emission decreases by 3–4.5%. At the same time, the tightening of carbon quotas (coefficient increased from 0.78 to 0.84) promoted the output of gas units to increase by 70 MWh, verifying the synergistic emission reduction effect of the “total control + market incentive” policy. Economic–environmental tradeoff analysis shows that high-cost inputs are positively correlated with the proportion of renewable energy, and carbon emissions are significantly negatively correlated with the proportion of green certificates (correlation coefficient −0.79). This study emphasizes that dynamic adjustments of carbon quota and green certificate targets can avoid diminishing marginal emission reduction efficiency, while the independent carbon price mechanism needs to enhance its linkage with economic targets through policy design. This framework provides theoretical support and a practical path for decision-makers to design a flexible market mechanism and build a multi-energy complementary system of “coal power base load protection, gas peak regulation, and renewable energy supplement”. Full article

Improving forest carbon sink efficiency (FCSE) is the key to mitigating climate change and achieving sustainable forest resource management in China. However, current research on FCSE remains predominantly focused on static perspectives and singular linear effects. Based on panel data from 30 provinces (autonomous regions and municipalities) in China from 2008 to 2022, this study integrated the super-efficiency Slack-Based Measure (SBM)-Malmquist–Luenberger (ML) model, spatial autocorrelation analysis, and dynamic fuzzy set qualitative comparative analysis (fsQCA) to reveal the spatiotemporal differentiation characteristics of FCSE and the multi-factor synergistic driving mechanism. The results showed that (1) the average value of the FCSE in China was 1.1. Technological progress (with an average technological change of 1.21) is the core growth driver, but the imbalance of technological efficiency change (EC) among regions restricts long-term sustainability. (2) The spatial distribution exhibited a U-shaped gradient pattern of “eastern—southwestern”, and the synergy effect between nature and economy is significant. (3) The dynamic fsQCA identified three sustainable improvement paths: the “precipitation–economy” collaborative type, the multi-factor co-creation type, and “precipitation–industry-driven” type; precipitation was the universal core condition. (4) Regional differences exist in path application; the eastern part depends on economic coordination, the central part is suitable for industry driving, and the western part requires multi-factor linkage. By introducing a dynamic configuration perspective, analyzing FCSE’s spatiotemporal drivers. We propose a sustainable ‘Nature–Society–Management’ interaction framework and region-specific policy strategies, offering both theoretical and practical tools for sustainable forestry policy design. Full article

With the increasing frequency of extreme weather events, global concerns regarding climate change have intensified, with carbon dioxide widely recognized as the primary driver of global warming and climate disruption. It is necessary to investigate how to develop industries to meet the constant GDP growth and minimum carbon emissions. This study investigates the optimization of industrial structure under China’s ‘Dual Carbon’ Goal in Guangdong Province from 2012 to 2017, employing a multi-objective programming model. Using the input–output table, carbon emissions across 42 industries are calculated based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission factor method. According to Hirschman’s theory of industrial interdependence, the economic and carbon emission linkage coefficients between these industries are obtained by calculating the Ghosh inverse matrix and the Leontief inverse matrix to analyze the economic forward and backward linkage of the industries, as well as the carbon emission forward and backward linkage. The impact of industry input and output on the urban economy and the resulting carbon emission problems are discussed, and industries are divided into encouraged and restricted industries. Using a multi-objective programming model, the expected final demand, changes in final demand, and expected carbon emissions of these industries under the ‘Dual Carbon’ Goal, with the target of maintaining the same economic growth rate and promoting carbon reduction, are analyzed. The results show that most industries in Guangdong Province need to reduce final demand, including the highest carbon-emitting industries and industries that are relatively restricted by scale in development. The policy implications of optimizing the industrial structure to reduce carbon emissions are provided. Full article

Understanding the spatial association network structure and carbon balance zoning of land-use carbon emissions (LUCEs) is essential for guiding regional environmental management. This study constructs a LUCE spatial association network for Hubei Province using a modified gravity model to uncover the spatial linkages in carbon emissions. Carbon balance zones are delineated by integrating LUCE network characteristics with economic and ecological indicators. To further examine the network dynamics, link prediction algorithms are employed to anticipate potential emission connections, while quadratic assignment procedure (QAP) regression analyzes how intercity differences in socioeconomic, ecological, and land-use attributes influence LUCE connectivity. The results reveal a pronounced core–periphery structure, with potential carbon spillover pathways extending toward both eastern and western cities. Based on the carbon balance analysis, six functional zones are identified, each aligned with targeted collaborative mitigation strategies. The QAP results indicate that intercity differences in innovation capacity, industrial structure, and economic development are positively associated with the formation of LUCE spatial networks, whereas disparities in urbanization level, government expenditure, and construction land use are negatively associated with LUCE connectivity. This study provides a differentiated governance framework to address the dual challenges of carbon emissions and land-use transformation in agro-urban regions. Full article

Integrating Electric Vehicle (EV) charging stations into buildings is becoming increasingly important due to the rapid growth of private EV ownership and prolonged parking durations in residential areas. This paper proposes robust, building-integrated charging solutions that combine mobile energy storage systems (ESSs), station linkage data, and traffic volume data. The proposed system promotes eco-friendly EV usage, flexible energy management, and carbon neutrality through a polyfunctional Vehicle-to-Grid (V2G) architecture that integrates decentralized energy networks. Two core strategies are implemented: (1) configuring Virtual Power Plant (VPP)-based charging packages tailored to station types, and (2) utilizing EV batteries as distributed ESS units. K-means clustering based on spatial proximity and energy demand is followed by heuristic algorithms to improve the efficiency of mobile ESS operation. A three-layer framework is used to assess improvements in energy demand distribution, with demand-oriented VPPs deployed in high-demand zones to maximize ESS utilization. This approach enhances station stability, increases the load factor to 132.7%, and reduces emissions by 271.5 kgCO₂. Economically, the system yields an annual benefit of USD 47,860, a Benefit–Cost Ratio (BCR) of 6.67, and a Levelized Cost of Energy (LCOE) of USD 37.78 per MWh. These results demonstrate the system’s economic viability and resilience, contributing to the development of a flexible and sustainable energy infrastructure for cities. Full article

This study focuses on the shift to a circular economy (CE) in the textile, apparel, and fashion (TAF) sectors, which generate tons of waste annually. Thus, embracing CE practices is essential for contributing to UN Sustainable Development Goals. This study employs a mixed-methods approach, integrating PRISMA for systematic literature selection, BERTopic modeling and AI-driven SDG mapping, and case study analysis to explore emerging CE themes, implemented circular practices, and systemic barriers. Machine-learning-based SDG mapping reveals strong linkages to SDG 9 and SDG 12, emphasizing technological advancements, industrial collaborations, and circular business models. Moderately explored SDGs, namely, SDG 8, SDG 6, and SDG 7, highlight research on labor conditions, water conservation, and clean energy integration. Reviewing 655 peer-reviewed papers, the BERTopic modeling extracted six key themes, including sustainable recycling, circular business models, and consumer engagement, whereas case studies highlighted regulatory frameworks, stakeholder collaboration, and financial incentives as critical enablers. The findings advance institutional theory by demonstrating how certifications, material standards, and regulations drive CE adoption, reinforcing SDG 12 and SDG 16. The natural resource-based view is extended by showing that technological resources alone are insufficiently aligned with SDG 9. Using the Antecedents–Decisions–Outcomes framework, this study presents a structured, AI-driven roadmap for scaling CE in the TAF industry, addressing systemic barriers, and supporting global sustainability goals, highlighting how multistakeholder collaboration, digital traceability, and inclusive governance can improve the impact of CE. The results recommend that CE strategies should be aligned with net-zero targets, carbon credit systems, and block-chain-based supply chains. Full article

Guided by China’s “Dual Carbon” targets, the construction of its carbon market advances steadily. As a key policy mechanism for promoting emissions reduction and sustainable development, the emissions trading system plays a vital role in the national green transition strategy. Nonetheless, significant regional disparities exist in carbon emissions, and carbon allowance prices are subject to considerable fluctuations. This study examines the spatiotemporal evolution of China’s carbon emissions, investigating their distribution patterns across different regions. Furthermore, it analyzes the spatiotemporal changes in carbon allowance prices, focusing on their fluctuation patterns and spatial distribution, particularly regional differences in carbon market prices. This study focuses on the interplay between carbon emissions and carbon allowance prices, conducting an in-depth investigation into their interaction mechanisms. Using Shanghai as a case study, we construct a Vector Autoregression (VAR) model to empirically assess the dynamic impact of carbon emissions on carbon prices and their associated feedback effects. Subsequently, we propose policy recommendations for optimizing carbon market operations. This study enhances carbon markets’ functionality as climate governance tools, providing empirical and theoretical foundations for advancing low-carbon transitions and Sustainable Development Goals (SDGs). Full article

This study explores the spatiotemporal dynamics of SOC and microbial-mediated mechanisms in the Yellow River Delta wetlands. Using redundancy analysis and microbial community profiling, we show that vegetation drives distinct SOC storage patterns: Phragmites australis ecosystems exhibit the highest SOC sequestration, followed by Suaeda salsa and Tamarix chinensis habitats, where salt-tolerant taxa like Desulfobacterota and Halobacteriaota promote short-term carbon storage via anaerobic metabolism. The microbial community structure is shaped by both vegetation-induced microhabitats and environmental gradients: SOC and total nitrogen dominate community assembly, while electrical conductivity, pH, and sulfur/nitrogen nutrients regulate spatiotemporal differentiation. Seasonal turnover drives the reorganization of microbial community structures, shaping the dynamic equilibrium of carbon pools. Seasonal DOC dynamics, linked to tidal fluctuations and exogenous carbon inputs, highlight hydrology’s role in modulating active carbon pools. These findings reveal tight linkages among vegetation, microbial functional guilds, and soil biogeochemistry, critical for wetland carbon sequestration. Full article