Search Results (126)

The low-carbon transition of the global energy system is an urgent necessity to address climate change and meet growing energy demand. As a major source of energy consumption and emissions, buildings play a key role in this transition. This study systematically analyzes the flexible resources of building energy systems and vehicle-to-grid (V2G) interaction technologies, and mainly focuses on the regulation characteristics and coordination mechanisms of distributed energy supply (renewable energy and multi-energy cogeneration), energy storage (electric/thermal/cooling), and flexible loads (air conditioning and electric vehicles) within regional energy systems. The study reveals that distributed renewable energy and multi-energy cogeneration technologies form an integrated architecture through a complementary “output fluctuation mitigation–cascade energy supply” mechanism, enabling the coordinated optimization of building energy efficiency and grid regulation. Electricity and thermal energy storage serve as dual pillars of flexibility along the “fast response–economic storage” dimension. Air conditioning loads and electric vehicles (EVs) complement each other via thermodynamic regulation and Vehicle-to-Everything (V2X) technologies, constructing a dual-dimensional regulation mode in terms of both power and time. Ultimately, a dynamic balance system integrating sources, loads, and storage is established, driven by the spatiotemporal complementarity of multi-energy flows. This paper proposes an innovative framework that optimizes energy consumption and enhances grid stability by coordinating distributed renewable energy, energy storage, and flexible loads across multiple time scales. This approach offers a new perspective for achieving sustainable and flexible building energy systems. In addition, this paper explores the application of demand response policies in building energy systems, analyzing the role of policy incentives and market mechanisms in promoting building energy flexibility. Full article

Global low-carbon innovation networks face increasing vulnerabilities amid growing geopolitical tensions and technological competition. The interdependent structure of low-carbon innovation networks and the risk propagation dynamics within them remain poorly understood. This study investigates vulnerability patterns by constructing a two-layer interdependent network model based on Chinese low-carbon patent data, comprising a low-carbon collaboration network of innovation entities and a low-carbon knowledge network of technological components. Applying dynamic shock propagation modeling, we analyze how risks spread within and between network layers under various shocks. Our findings reveal significant differences in vulnerability distribution: the knowledge network consistently demonstrates greater susceptibility to cascading failures than the collaboration network, reaching complete system failure, while the latter maintains partial resilience, with resilience levels stabilizing at approximately 0.64. Critical node analysis identifies State Grid Corporation as a vulnerability point in the collaboration network, while multiple critical knowledge elements can independently trigger system-wide failures. Cross-network propagation follows distinct patterns, with knowledge-network failures consistently preceding collaboration network disruptions. In addition, propagation from the collaboration network to the knowledge network showed sharp transitions at specific threshold values, while propagation in the reverse direction displayed more gradual responses. These insights suggest tailored resilience strategies, including policy decentralization approaches, ensuring technological redundancy across critical knowledge domains and strengthening cross-network coordination mechanisms to enhance low-carbon innovation system stability. Full article

This study introduces a novel control strategy tailored to nonlinear systems with non-minimum phase (NMP) characteristics. The framework leverages reinforcement learning within a cascade control architecture that integrates an Actor–Critic structure. Controlling NMP systems poses significant challenges due to the inherent instability of their internal dynamics, which hinders effective output tracking. To address this, the system is reformulated using the Byrnes–Isidori normal form, allowing the decoupling of the input–output pathway from the internal system behavior. The proposed control architecture consists of two nested loops: an inner loop that applies input–output feedback linearization to ensure accurate tracking performance, and an outer loop that constructs reference signals to stabilize the internal dynamics. A key innovation in this design lies in the incorporation of symmetry principles observed in both system behavior and control objectives. By identifying and utilizing these symmetrical structures, the learning algorithm can be guided toward more efficient and generalized policy solutions, enhancing robustness. Rather than relying on classical static optimization techniques, the method employs a learning-based strategy inspired by previous gradient-based approaches. In this setup, the Actor—modeled as a multilayer perceptron (MLP)—learns a time-varying control policy for generating intermediate reference signals, while the Critic evaluates the policy’s performance using Temporal Difference (TD) learning. The proposed methodology is validated through simulations on the well-known Inverted Pendulum system. The results demonstrate significant improvements in tracking accuracy, smoother control signals, and enhanced internal stability compared to conventional methods. These findings highlight the potential of Actor–Critic reinforcement learning, especially when symmetry is exploited, to enable intelligent and adaptive control of complex nonlinear systems. Full article

Under China’s dual-carbon strategy, the construction sector still lacks a systematic quantitative view of what drives its shift to a circular economy. This study couples the Decision-Making Trial and Evaluation Laboratory (DEMATEL) with Total Adversarial Interpretive Structural Modeling (TAISM) to build a weighted, multi-layer model of the policy–market–organization–technology chain. DEMATEL measures causal strengths, and TAISM arranges the variables into five levels without subjective thresholds, revealing a five-stage activation pathway. Fiscal incentives and regulations start the cascade; market demand amplifies their effect into a “resonant resilience” mechanism that improves cost performance. Robustness tests show 87% hierarchy stability and causal variation within ±0.6%. Sensitivity checks indicate that policy support must supply at least 30% of total network weight, because market capital alone cannot meet circular-construction costs. A three-tier intervention—policy incentives, financial amplification, and digital decomposition via green finance, BIM, and material passports—is therefore recommended. Full article

In the context of rapid urbanization, traditional villages in the Weibei Loess Plateau gully region are facing compounded pressures from social structure disruption and physical space reconstruction. It is urgent to deeply analyze the influence mechanism of social relations on spatial adaptability. This study attempts to construct an analytical framework that couples social relationships with village spatial development. With Tangjia Village in the gully region of the Weibei Loess Plateau as an example, the study integrated various data sources such as satellite imagery, interviews, and policy documents. Through social network analysis and an improved cascade failure model, the spatial adaptation processes and characteristics based on changes in kinship, occupational ties, and geographical networks were explored. The findings indicate that (1) before 2001, kinship networks led to the formation of a monocentric settlement structure. From 2001 to 2011, occupational ties fostered the differentiation of industrial and residential zones. After 2011, geographical networks drove the multifunctional integration of space. (2) Clan-based settlement zones (consisting of 80 kinship nodes) and core cultural tourism facilities are key units in maintaining spatial adaptability. The research reveals the impact mechanism of social network fission on spatial function reorganization and proposes adaptive planning strategies, aiming to provide theoretical and practical value for the coordinated governance of society and space in traditional villages. Full article

Post-earthquake fires (PEFs) represent a complex, cascading hazard in which seismic damage creates ignition conditions that can overwhelm urban infrastructure and severely compromise structural integrity. Despite growing scholarly attention, the literature on PEFs remains fragmented across disciplines, lacking a consolidated understanding of structural vulnerabilities, urban-scale impacts, and response strategies. This study presents a systematic and thematic synthesis of 54 peer-reviewed articles, identified through a PRISMA-guided screening of 151 publications from the Web of Science Core Collection. By combining bibliometric mapping with thematic clustering, the review categorizes research into key methodological domains, including finite element modeling, experimental testing, probabilistic risk analysis, multi-hazard frameworks, urban simulation, and policy approaches. The findings reveal a dominant focus on structural fire resistance, particularly of seismically damaged concrete and steel systems, while highlighting emerging trends in sensor-based fire detection, AI integration, and urban resilience planning. However, critical research gaps persist in multi-hazard modeling, firefighting under partial collapse, behavioral responses, and the integration of spatial, infrastructural, and institutional factors. This study proposes an interdisciplinary research agenda that connects engineering, urban design, and disaster governance to inform adaptive, smart-city-based strategies for mitigating fire risks in seismic zones. This work contributes a comprehensive roadmap for advancing post-earthquake fire resilience in the built environment. Full article

Amid escalating global climate crises and the urgent imperative to meet the Paris Agreement’s carbon neutrality targets, the steel industry—a leading contributor to global greenhouse gas emissions—confronts unprecedented challenges in driving sustainable industrial transformation through innovative low-carbon steelmaking technologies. This paper examines decarbonization technologies across three stages (source, process, and end-of-pipe) for two dominant steel production routes: the long process (BF-BOF) and the short process (EAF). For the BF-BOF route, carbon reduction at the source stage is achieved through high-proportion pellet charging in the blast furnace and high scrap ratio utilization; at the process stage, carbon control is optimized via bottom-blowing O₂-CO₂-CaO composite injection in the converter; and at the end-of-pipe stage, CO₂ recycling and carbon capture are employed to achieve deep decarbonization. In contrast, the EAF route establishes a low-carbon production system by relying on green and efficient electric arc furnaces and hydrogen-based shaft furnaces. At the source stage, energy consumption is reduced through the use of green electricity and advanced equipment; during the process stage, precision smelting is realized through intelligent control systems; and at the end-of-pipe stage, a closed-loop is achieved by combining cascade waste heat recovery and steel slag resource utilization. Across both process routes, hydrogen-based direct reduction and green power-driven EAF technology demonstrate significant emission reduction potential, providing key technical support for the low-carbon transformation of the steel industry. Comparative analysis of industrial applications reveals varying emission reduction efficiencies, economic viability, and implementation challenges across different technical pathways. The study concludes that deep decarbonization of the steel industry requires coordinated policy incentives, technological innovation, and industrial chain collaboration. Accelerating large-scale adoption of low-carbon metallurgical technologies through these synergistic efforts will drive the global steel sector toward sustainable development goals. This study provides a systematic evaluation of current low-carbon steelmaking technologies and outlines practical implementation strategies, contributing to the industry’s decarbonization efforts. Full article

Antimicrobial resistance (AMR) has emerged as a critical global public health threat, exacerbating healthcare burdens and imposing substantial economic costs. Currently, AMR contributes to nearly five million deaths annually worldwide, surpassing mortality rates of any single infectious disease. The economic burden associated with AMR-related disease management is estimated at approximately $730 billion per year. This review synthesizes current research on the mechanisms and multifaceted drivers of AMR development and dissemination through the lens of the One Health framework, which integrates human, animal, and environmental health perspectives. Intrinsic factors, including antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs), enable bacteria to evolve adaptive resistance mechanisms such as enzymatic inactivation, efflux pumps, and biofilm formation. Extrinsic drivers span environmental stressors (e.g., antimicrobials, heavy metals, disinfectants), socioeconomic practices, healthcare policies, and climate change, collectively accelerating AMR proliferation. Horizontal gene transfer and ecological pressures further facilitate the spread of antimicrobial-resistant bacteria across ecosystems. The cascading impacts of AMR threaten human health and agricultural productivity, elevate foodborne infection risks, and impose substantial economic burdens, particularly in low- and middle-income countries. To address this complex issue, the review advocates for interdisciplinary collaboration, robust policy implementation (e.g., antimicrobial stewardship), and innovative technologies (e.g., genomic surveillance, predictive modeling) under the One Health paradigm. Such integrated strategies are essential to mitigate AMR transmission, safeguard global health, and ensure sustainable development. Full article

This study posits the need for a conceptual multi-risk management approach for fresh produce, an essential product category for societal resilience and one constantly affected by climate change, policy volatility, and geopolitical disruptions. The research started with a literature-informed typological risk mapping, leading to Gephi ver 0.10.1 visualizations of networks related to this trade. Network analysis using 2024 bilateral trade data revealed a core–periphery topology, with the United States, Spain, and the Netherlands as central hubs. A gravity-based simulation model was, lastly, used to address the following question: what structural vulnerabilities and flow-based sensitivities define the global fresh produce trade, and how do they respond to simulated multi-risk disruptions? The model used the case of the USA as a global trade hub and induced two compounding risks: a protectionist tariff policy shock and a climate-related shock to its main supplier. The conclusion was that the fragility in the fresh produce trade enhances the cascading effects that any risk event may have across the environmental, economic, and social sustainability dimensions. This paper emphasizes the need for anticipatory governance, the diversification of trade partners, and investment in cold chain resilience, offering a means for policymakers to acknowledge the risk and mitigate the threats to the increasingly fragile fresh produce trade. Full article

This longitudinal study applies decade-spanning socioeconomic indicators (2013–2022) from the Beijing–Tianjin–Hebei urban agglomeration. An integrated analytical framework was developed, merging the super-efficiency slack-based measurement (SBM) methodology with entropic weighting techniques to quantify tourism efficiency and economic development. Subsequent phases employed a multi-method analytical cascade: coupling coordination assessment modeling for system interaction analysis, standard deviation ellipses for spatial dispersion characterization, and Markovian transition matrices for temporal pattern identification. The investigation concludes with evolutionary trajectory projections using gray system forecasting GM(1,1) modeling. The analytical findings reveal the following patterns: (1) Within the Beijing–Tianjin–Hebei metropolitan cluster, tourism efficiency demonstrates a consistent upward trajectory, manifesting spatial differentiation characteristics characterized by a dual-core structure centered on Tianjin and Baoding, with higher values observed in northwestern areas compared to southeastern regions. Concurrently, regional disparities exhibit progressive convergence over temporal progression. (2) The level of economic development in the Beijing–Tianjin–Hebei city cluster has been rising steadily, demonstrating a geospatial distribution of ‘central concentration with peripheral attenuation, with the north-east being better than the southwest’, and the gap between the regional differences has become broader over time. (3) The coupling between tourism efficiency and the level of economic development in the Beijing–Tianjin–Hebei city cluster has generally improved, with Beijing and Tianjin predominantly in a coordinated regime, and some cities in Hebei Province about to shift from dysfunctional to coordinated, and, spatially, the coupling and coordination in northern sectors demonstrate superior performance compared to southern counterparts nationally. (4) The coupling coordination degree of the Beijing–Tianjin–Hebei city cluster in the next eight years is predicted by the gray GM(1,1) prediction model and the overall continuation of the growth trend of the Beijing–Tianjin–Hebei city cluster over the past ten years, thus verifying the importance of the regional integrated policy frameworks in the system integration of the Beijing–Tianjin–Hebei metropolitan system. Full article

Riverine and lacustrine shorelines are crucial for human survival and development, but their natural and ecological environments are highly fragile and sensitive. Intensified human activities have placed unprecedented pressure on the shoreline ecosystem of the Yangtze River Basin. This study investigates the degradation of river and lake shorelines and its cascading effects on ecological service functions. Using Sentinel-2 as the primary data source, we analyzed land use/cover changes and ecosystem service values (ESV) in the Huanggang and Taihu sections of the Yangtze River from 2018 to 2022. The supervised classification results using the support vector machine (SVM) algorithm exceeded 95% accuracy. In the Huanggang section, vegetation was significantly converted into cultivated land and built-up areas (−6.17 km²), while in the Taihu section, water bodies were largely transformed into agricultural land (−3.77 km²). In this study, we quantified changes in ESV using the unit area equivalent factor method, adjusted based on net primary productivity, precipitation, and the soil conservation coefficient. The results indicate that the ESV ranking in both sections follows the order: water conservation > environmental purification > biodiversity > soil conservation. From 2018 to 2022, the ESV in the Huanggang section declined due to forest and grassland loss and an increase in bare land. In contrast, ecological restoration and habitat protection policies contributed to an improvement in ecosystem service functions in the Taihu section, with various ESV components increasing as follows: soil conservation (8.79%) > biodiversity (6.67%) > environmental purification (5.98%) > water conservation (5.52%). These findings provide valuable insights for decision-making in the protection and management of the Yangtze River Basin ecosystem. Full article

The Arctic is undergoing unprecedented transformations with implications for regional ecosystems, Indigenous communities, and global climate systems. Ocean heat transport, permafrost thawing, and ice–albedo interactions are some of the feedback mechanisms that contribute to the increase in average temperatures in the Arctic. These processes increase the risks associated with climate change globally by speeding up the loss of sea ice, changes in biodiversity, and greenhouse gas emissions. This review synthesises recent advances in Arctic climate science, focusing on the drivers and feedback mechanisms of Arctic amplification, its cascading impacts on ecosystems and socioeconomic systems, and emerging governance challenges. It highlights critical knowledge gaps, specifically regarding the importance of Indigenous knowledge and interdisciplinary approaches in climate adaptation strategies. This study emphasises the need for inclusive, transformative, and collaborative approaches by analysing governance frameworks, climate policies, and community resilience initiatives. Innovative adaptation strategies are suggested, such as ecosystem-based adaptations, climate-resilient infrastructure, and the switch to renewable energy to address these issues. Arctic-specific governance recommendations are proposed to develop sustainable solutions that preserve its ecology while reducing its global effects by filling research gaps and promoting international collaboration. The future of the Arctic is not merely a regional issue but also a global one, requiring swift and coordinated action to address climate challenges. Full article

Recent years have been exceptionally turbulent due to various crises such as COVID-19, wars, and natural disasters. We conduct a systematic literature review to address the current state of the regional economic resilience literature, a topic regaining significance amid recent global crises. Considering the findings, we not only conduct the most up-to-date analysis of resilience types but also innovate previous research by collecting and processing data on the spatial and income features of regions, providing statistics about shock coverage, and sharing insights into region types. Additionally, we supplement the systematic literature analysis methodology by experimenting with large language models and defining new search strategies. The results show that most of the literature covers European countries, while that covering all other countries is far behind. Empirical coverage comes from high- and upper-middle-income countries (~97% of research), highlighting the lack of analysis on lower-middle- and low-income countries. This brings into question the applicability of regional resilience policies worldwide. The latest papers still mainly analyze the Great Recession, the most covered shock in the regional economic resilience literature. Not all authors have turned their attention to more recent crises. Finally, we believe future research should focus more on compound resilience—how regional economies cope with cascading or simultaneous shocks. Full article

With the popularity of new-energy vehicles, the recovery and reuse of lithium-ion battery (LIB) resources have become topics of great concern. This study explores the risks of the lithium resource chain in terms of supply–demand balance and lithium resource criticality. We propose a prediction algorithm for lithium production based on reverse-order MT-EGM-SD (metabolism–even grey model–system dynamics), upon which a system dynamics model for lithium resource recycling and reuse is constructed. We use dynamic simulation to evaluate the benefits of lithium resource recovery and the effects of different LIB recovery strategies. The results show that LIB recycling strategies, such as enhancing subsidy levels and strengthening public awareness initiatives, can significantly increase lithium resource recovery rates. From a medium- and long-term perspective, however, the technological progress strategy can greatly reduce lithium consumption intensity in the battery. Cascade use policy has significant economic benefits, but it delays the recycling of secondary raw materials. Under the joint strategy with the best resource efficiency (stringent government recycling regulations and significant advancements in battery production technology), the lithium supply–demand balance and the lithium resource recovery rate increase by 301.89% and 795.65%, respectively. Meanwhile, lithium resource chain risk, lithium criticality, and actual lithium demand decrease by 18.77%, 18.86%, and 75.11%, respectively. Full article

This study considers ways in which workers can be allocated dynamically in the few hours before the truck departure to flush the system of orders that are almost completed, thereby increasing the service performance of the system. To implement a worker allocation policy correctly, we need to answer the following questions: how many workers should we move, and when? We present the optimal number of workers required and the switching time for the proposed three dynamic worker reallocation policies through simulation experiments. The number of workers required was determined by the difference between the current and target probability of success of an order in the system based on the state-dependent sojourn time distribution, and the performance of the system was measured by Next Scheduled Departure (NSD). We find that the policies with late switching times and higher target probability of success have a greater effect on customer satisfaction. Our results suggest that it is possible to improve service performance significantly, in some conditions, by moving the right number of workers to the right place at the right time. Full article