Search Results (56)

Quantifying the direction, strength and temporal clustering of cross-border financial risk contagion calls for methods that go beyond linear correlation. We suggest a two-layer framework that brings together transfer entropy and a multivariate Hawkes self-exciting point process on a time-varying, directed, weighted network. In the first layer, one-to-one transfer entropies of sovereign credit default swap spreads are estimated with a bias-corrected k nearest neighbour estimator, and this step detects nonlinear and directional information transfer between spreads. The second layer is a multivariate Hawkes process that models how extreme loss events arrive and mutually excite one another across countries, and it gives an excitation intensity matrix, encoding the way a tail event in one country raises the likelihood of an instantaneous hazard occurring in another. By merging these two layers, we obtain a composite, directed, weighted adjacency matrix in which the weights of the edges reflect both information flow and event clustering. We introduce a network-level contagion intensity index and split it into direct, indirect and feedback terms using the graph Laplacian spectrum. Von Neumann graph entropy together with the spectral gap ratio serve as entropy-based measures of the complexity and fragility of the evolving network. We validate the choice of Shannon-type entropy through a Tsallis q-sensitivity analysis, and we verify the nonlinear dependence structure of the data using BDS tests and maximal Lyapunov exponent estimates. Three empirical findings emerge from analysing 20 sovereign CDS markets from January 2015 to December 2025: (i) directional risk spillover signals derived based on transfer entropy are more timely than those derived from variance decomposition; (ii) the Hawkes excitation component amplifies measured contagion intensity by 35 to 58 percent during the COVID-19 shock and the 2022 European energy crisis relative to a transfer-entropy-only baseline; (iii) von Neumann graph entropy reaches historically extreme values 7 to 12 trading days before the peak drawdown in a Global Sovereign Bond Index. These results hold across rolling window lengths, significance thresholds, alternative entropy functionals and alternative Hawkes kernels. Full article

Most Transmission System Operators (TSOs) rely on seasonally static line rating models based on extreme weather conditions to determine the transmission capacity of power lines. These conservative rating approaches constrain grid capacity, limiting the integration of new renewable energy sources and delaying the transition to a more sustainable power system. Furthermore, they restrict cross-border transmission capacity between market zones, leading to “false” congestion and unnecessary market splitting. Market splitting can result in economic losses for market participants due to price differences between market zones and the potential curtailment of renewable generation. The adoption of Dynamic Line Rating (DLR) models can help avoid the need for new transmission infrastructure, reduce market splitting and false congestion, and mitigate line degradation in a cost-effective manner. The OptiRES.Lines tool integrates several DLR models, enabling their simulation and visualization through a Geographic Information System (GIS) interface. These dynamic rating models are combined with an Optimal Power Flow (OPF) model to assess: (1) the long-term potential for integrating new power plants at different grid locations; (2) the available cross-border transmission capacity between market zones; and (3) short-term grid congestion. The tool was tested in two regions of Portugal and demonstrated a significant increase in the grid’s capacity to accommodate additional renewable generation, thereby contributing to a more sustainable power system. The results showed that, although DLR alone indicated an increase in transmission line capacity during approximately 70% of the analysed period, the inclusion of OPF analysis revealed that DLR reduced line loading factors during 95% of the time analysed, highlighting its broader system-level benefits. Full article

The North Sea is becoming a shared renewable energy space in which offshore wind deployment, grid planning, market operation and environmental governance increasingly cross borders. This article asks how wind-resource complementarity can inform legal and institutional design for cross-border offshore wind cooperation. It combines a five-year representative-point wind-resource screening analysis using NASA POWER hourly data from 2021 to 2025 with functional legal–institutional analysis. The empirical analysis covers seven offshore or near-offshore representative screening points, hub-height correction to 100 m and 150 m, a wind-power proxy and wind-power-density proxy, low-wind frequency and low-wind event duration, monthly and interannual variability, pairwise correlation, CWCI and weighting sensitivity. The representative-point results suggest a mean 100 m corrected wind-speed range of 8.52 to 9.88 m/s, 4 m/s low-wind frequencies of 8.69% to 12.64%, and a maximum 4 m/s low-wind event of 173.0 h at NO_SOUTH. The baseline CWCI screening identifies DK West–BE Coast, DK West–FR Channel and UK East–FR Channel as leading within-sample pairs. The legal analysis uses these results as screening evidence for questions of data compatibility, hub-height assumptions, low-wind consultation, hybrid offshore grid governance, market coordination, cumulative environmental assessment, investment regulatory space and crisis dispute prevention. The article proposes an operational five-pillar framework with institutions, instruments, implementation steps and compliance pathways. It should be read as an exploratory evidence-to-law screening analysis, not a definitive wind-resource assessment, turbine-output model, capacity-factor estimate or grid-dispatch simulation. Full article

Against the backdrop of the deep advancement of the carbon peak and carbon neutrality goals and the superposition of the transportation power strategy, leveraging the spatial restructuring of highway networks to optimize the low-carbon layout of county-level industries has become a crucial lever for balancing economic quality improvement with carbon intensity control. This study selects panel data from 129 counties in Yunnan Province spanning 2015–2024, constructing a comprehensive highway network development index from four dimensions: highway density, road network connectivity, weighted hierarchical structure, and county accessibility. Using a two-way fixed effects benchmark model, a stepwise mediation effect testing framework, and a regional heterogeneity identification strategy, the paper systematically examines the marginal effects, transmission pathways, and spatially differentiated characteristics of highway network development on county-level industrial carbon emission intensity. Key findings are as follows: Enhanced highway network development significantly suppresses the increase in county-level industrial carbon emission intensity, and a well-developed road network can provide long-term empowerment for the low-carbon transformation of county-level industries. Mechanism analysis confirms that highway network development reduces emissions through two core pathways: first, a direct emission reduction effect achieved by optimizing the county-wide freight organization system, reducing inefficient transport energy consumption, and improving overall transport efficiency; second, an indirect low-carbon enabling effect realized by breaking down administrative barriers in county markets, lowering cross-regional business transaction costs, deepening industrial division of labor and collaboration, and forcing resource allocation improvements. Heterogeneity analysis reveals that the low-carbon dividends of highway network development exhibit significant gradient differentiation: the emission reduction enabling effect is strongest in counties within the Central Yunnan urban agglomeration, followed by cultural tourism counties in western Yunnan and border counties in southern Yunnan, with the weakest marginal enabling effect observed in traditional agricultural counties in northeastern Yunnan. Full article

Achieving carbon neutrality requires simultaneous advances in both the quantity and quality of low-carbon technology innovation (LCTI). This paper uses a country–industry–year three-dimensional panel dataset covering 25 EU member states and 39 two-digit NACE Rev. 2 industries over the period 2003–2020 to examine the effects of energy market integration (EMI) on LCTI quantity and quality. An EMI index is constructed based on cross-national energy price dispersion, and the analysis employs Poisson pseudo-maximum likelihood estimation with three-way fixed effects, complemented by a Bartik instrumental variable and double/debiased machine learning as supporting robustness evidence. Results show that: (1) EMI exerts significant positive effects on both LCTI quantity and quality; (2) Mechanism tests reveal that EMI operates through two channels: expansion of energy R&D investment and intensification of cross-border knowledge spillovers; (3) Heterogeneity analysis shows that the promoting effects are concentrated in countries with adequate R&D investment and active energy market competition, and in industries with low emission intensity and low energy intensity. These findings suggest that deepening regional energy market integration constitutes a meaningful institutional complement to conventional low-carbon innovation policy. Full article

This paper examines source-conditioned spillovers and tail dependence in Belt and Road Initiative equity markets under China-related equity distress and WTI oil-price-decline distress. We define source-conditioned spillovers as incremental changes in pairwise dependence relative to a median-threshold benchmark, and source-conditioned tail dependence as the nonlinear higher-order component of these changes. Using a DCC-GARCH model with multivariate generalized hyperbolic innovations, we construct a linear co-moment layer and a nonlinear tail-dependence layer for 32 equity markets from 2007 to 2025. The resulting annual country-level exposure measures are then related to macroeconomic, China-linked, and oil-linked characteristics through benchmark fixed-effects and source-matched regressions. The empirical results imply that the linear layer mainly reflects background synchronization, whereas the nonlinear layer captures selective tail-state amplification. SSEC-conditioned exposure is more visible in China-adjacent and regionally linked equity relationships, while WTI-conditioned exposure is more visible among intermediary receiving markets and in nonlinear oil-related episodes. The comparison after 2013 suggests that BRI equity markets became more vulnerable to energy driven tail risk, as WTI distress is more strongly associated with nonlinear downside amplification. SSEC distress mainly increases the common linear exposure channel, indicating broader regional synchronization rather than a persistent rise in nonlinear contagion. The framework provides a financial-stability diagnostic for sustainable-finance resilience by distinguishing routine cross-market synchronization from nonlinear downside exposure relevant to cross-border financing, infrastructure investment, and energy-transition-related capital allocation. Full article

The transition of thermal power systems toward lower-carbon electricity raises a critical strategic question: whether to rely on cross-border electricity imports or reactivate domestic nuclear capacity under supply constraints. This study examines the trade-offs between these alternatives within a sustainable finance framework. A contingent-claim model is developed in which a life insurer provides long-term financing to a biomass-energy supplier, a thermal power plant, and a nuclear power plant operating under carbon-pricing regulation. The framework links electricity-market decisions with financial risk valuation, allowing the joint effects of biomass utilization, carbon regulation, electricity imports, and nuclear-security risks to be evaluated. The results show that biomass integration and tighter carbon regulation reduce short-term profitability in thermal generation but support long-run decarbonization. Cross-border electricity imports improve system flexibility and reduce operational volatility, strengthening the financial position of thermal producers. In contrast, nuclear-security disruptions significantly increase default risk for nuclear assets, reflecting their exposure to operational and regulatory uncertainty. By integrating energy-transition strategies with contingent-claim valuation, the analysis highlights the role of financial intermediation in shaping investment incentives and risk allocation in the electricity sector. The findings suggest that coordinated policies combining market integration, low-carbon transition strategies, and stable financing mechanisms can enhance system resilience. Full article

Global decarbonization and the rapid growth of distributed energy resources increase the need for information-centric mechanisms that can support secure, scalable, cross-border coordination under heterogeneous technical and regulatory conditions. This paper proposes a Global Virtual Prosumer (GVP) framework that integrates IoT sensing, multi-agent coordination, and permissioned blockchain smart contracts to operationalize cross-border energy services as auditable service commitments rather than physical power exchange. Building on prior work that validated MAS-based power management and blockchain-secured operation within individual Virtual Prosumers, the present contribution lies in the cross-border coordination layer and its associated contractual and evaluation mechanisms, not in the constituent technologies themselves. A layered IoT–AI–blockchain architecture is introduced, where off-chain optimization produces allocations and admissibility indicators and on-chain contracts enforce identity, feasibility guards, delegation and partner-assignment rules, oracle verification, and settlement time compliance outcomes. The contractual lifecycle is formalized through four smart-contract algorithms covering trade registration, conditional delegation, cooperative fulfillment, and cross-border settlement with explicit failure semantics and event-based audit trails. The framework is evaluated on a global case study with seven Virtual Prosumers and quantified using contract-centric KPIs that capture registration time rejections, settlement success versus non-compliance, oracle-driven failure attribution, and full lifecycle traceability. The results demonstrate internal consistency of the proposed lifecycle and the practical value of KPI-driven accountability for cross-border energy service coordination. At the same time, the evaluation is based on synthetic parameterization and an emulated contract environment; realistic deployment constraints—including consensus latency, cross-region communication reliability, and regulatory overlap—are discussed as explicit limitations and directions for future empirical validation. Full article

The global energy transition demands solutions that balance intermittent renewable energy generation while decarbonizing heat and power sectors. Hydrogen has appeared as a versatile energy carrier, enabling sector coupling across electricity, heat, and industry. This work explores the integration of hydrogen into combined heat and power (CHP) systems, with a regional focus on Saarland, Germany. It depicts H₂-ready technologies including combustion engines, gas turbines, and fuel cells, and introduces a custom Python-based (Version 3.13) techno-economic optimization model to simulate multi-energy system operations. The analysis reveals that high hydrogen costs, electricity price volatility, and market design significantly constrain economic viability. However, Saarland’s industrial structure and cross-border infrastructure projects offer strategic opportunities for scalable hydrogen deployment. The article concludes with targeted recommendations for technology development, policy reform, and regional replication, positioning hydrogen CHP as a flexible and decarbonizing solution in energy-intensive regions. Full article

Against the backdrop of China’s dual-carbon goals and the global push toward net-zero emissions, Macao faces not only an innovation deficit but also the urgent need to reconfigure its economic structure toward green and low-carbon development. This study investigates collaborative innovation mechanisms within Macao’s technological ecosystem through the lens of new qualitative productivity, a paradigm emphasizing structural optimization and systemic innovation capacity. As a micro-jurisdiction within the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), Macao faces challenges due to its tourism-dependent economy and spatial constraints. Employing a qualitative methodology grounded in collaborative governance theory, the research combines theoretical framework construction with empirical case studies of technology enterprises, notably Enterprise B, to analyze stakeholder interactions, resource integration, and institutional dynamics. This study examines how collaborative technological innovation governance in a micro-jurisdiction can underpin net-zero and green supply chain transitions by mobilizing cross-border resources and institutional synergies. Key findings reveal a polycentric governance model involving government, enterprises, academic institutions, and civil society organizations. This model leverages cross-border synergies, platformization, and adaptive recalibration to overcome structural limitations. Results highlight tripartite drivers—policy incentives, market forces, and corporate strategies—that enhance innovation throughput. Despite advancements in institutional coordination, challenges persist, including low enterprise absorption of government funding, talent attrition, and fragmented academic–industrial linkages. The study proposes strategic recalibrations, such as refining policy architectures, strengthening industry–academia–research symbiosis, and optimizing transnational collaboration through Macao’s Lusophone networks. The findings provide governance insights for micro-jurisdictions seeking to align new qualitative productivity with decarbonization, renewable energy integration, and participation in regional green supply chains. Full article

Achieving Egypt’s 2035 renewable electricity targets presents substantial operational and institutional challenges, compounded by limited electricity trade across the Middle East and North Africa (MENA) region. This study applies a PLEXOS-based simulation framework that integrates short-term economic dispatch with the Projected Assessment of System Adequacy (PASA) to evaluate the system-level impacts of economically dispatched cross-border interconnections with Saudi Arabia, Libya, Jordan, and Sudan. The analysis also incorporates domestic flexibility measures, including five-minute dispatch, dynamic reserve requirements, and battery energy storage systems (BESS). Scenarios with renewable energy penetration levels of up to 50% are assessed using Egypt’s 2023 power system as the baseline. The results demonstrate that transitioning from a static, hourly, standalone operating framework to an integrated flexibility configuration—combining five-minute dispatch, 8 GW of economically dispatched cross-border interconnection capacity, and 8 GWh of BESS—yields substantial system-wide benefits at 50% renewable penetration. Loss-of-Load Probability declines from 96.48% to zero, ensuring full system adequacy, while total operational costs decrease by more than 45%, corresponding to annual savings of approximately USD 1.04 billion. Renewable energy curtailment is reduced by over 98%, enabling nearly 15 TWh of additional clean electricity generation, and CO₂ emissions fall by 11.6 million tons (≈40%). In addition, the operating-reserve shadow price—an indicator of reserve scarcity—declines to near zero, underscoring the effectiveness of coordinated regional dispatch and domestic flexibility in mitigating scarcity conditions. These findings provide robust evidence that integrated operational, temporal, and spatial flexibility can significantly accelerate renewable energy integration while strengthening system adequacy. The proposed framework offers an actionable and scalable blueprint for policy coordination and market reform in Egypt, with broader relevance for emerging power systems across the MENA region. Full article

Europe’s energy transition beyond 2025 faces a resilience gap as reconfigured pipeline flows, stricter methane rules, and rising variable renewables increase the need for seasonal flexibility and system adequacy. This study examines how Ukraine’s gas transmission network and underground gas storage—among the largest in Europe—can serve as a “seasonal battery” for the EU. We integrate a policy and market review with quantitative scenarios for 2026–2030. Methods include security-of-supply indicators (the rule that the system must keep operating even if its largest single infrastructure element fails, peak-day coverage, and winter adequacy), estimates of market-accessible storage volumes and withdrawal rates for European market participants, and a techno-economic screening of hydrogen-readiness comparing repurposing with new-build options. Methane intensity constraints and compliance with monitoring, reporting, and verification and leak detection and repair requirements are applied. The results indicate that reallocating part of Europe’s seasonal balancing to Ukrainian underground gas storage can enhance resilience to extreme winter demand and liquefied natural gas price shocks, reduce price volatility and the curtailment of variable renewables, and enable phased, cost-effective hydrogen corridors via repurposable pipelines and compressors. We outline a policy roadmap specifying transparent access rules, interoperable gas quality and methane standards, and risk mitigation instruments needed to operationalise cross-border storage and hydrogen-ready investments without carbon lock-in. Full article

Geomagnetic disturbances are an emerging sustainability challenge for modern, low-carbon and highly interconnected power systems, affecting both grid stability and market performance. We develop a deep causal neural network that fuses geomagnetic observatory measurements with national operational indicators and, via counterfactual inference, traces shock and no-shock trajectories to estimate instantaneous and cumulative impacts. Using Switzerland as a case, shocks significantly change national load, canton-level consumption, cross-border flows, and balancing prices. East–west disturbances have stronger effects than north–south, highlighting the role of grid topology. At the regional scale, the canton of Aargau shows pronounced cumulative consumption responses, revealing spatial heterogeneity. In cross-border exchanges, imports rise after shocks while exports contract and transit flows decline; balancing prices increase markedly, suggesting that market mechanisms can amplify physical stress into economic impacts. The approach goes beyond correlation and exposure metrics by providing system-level, decision-relevant effect sizes. The main contributions are as follows: (i) a deep causal framework that identifies and quantifies the causal effects of geomagnetic disturbances on grid operations and prices; (ii) topology-linked empirical evidence of directional and spatial asymmetries across national, canton-level, and cross-border indicators; and (iii) actionable levers for system operation and market design. These findings inform risk-aware reserve procurement, topology-aware dispatch, and cross-border coordination in highly interconnected, low-carbon grids, helping to enhance reliability, maintain affordability, and facilitate clean-energy integration. Full article

As a critical raw material in the semiconductor and new energy sectors, antimony is a strategic mineral resource for nations to safeguard industrial chain security. However, the scarcity of its resources and the complexity of its trade pattern underscore the urgency of antimony-related research. This study aims to reveal the structural characteristics of the global antimony trade network and explore the external factors influencing trade. Based on global antimony trade data from 2007 to 2022, the characteristics of the antimony trade network were analyzed using the complex network analysis method, and the influencing factors of antimony trade were examined via the fixed effects model. The results show that the global antimony trade network maintains a density of 0.05–0.06, with an average path length of 2.4–2.7 and a network diameter that mainly fluctuates between 5 and 6. The average clustering coefficient fluctuates within the range of 0.35–0.45. Overall, the network exhibits the characteristics of stable transmission efficiency, loose overall connectivity, and local agglomeration without a consistent upward or downward trend. Countries such as Germany, China, and the United States occupy core positions in the network. The fixed effects model indicates that GDP and LOGISTICS development are key factors promoting trade, while TARIFFS and REGULATORY policies have a significant inhibitory effect on trade. Therefore, ① Focus on the High-End Development of the Antimony Industry Chain and Promote the In-Depth Integration of Antimony Trade with the Semiconductor and New Energy Industries; ② Improve the Cross-Border Logistics and Warehousing System for Antimony Trade to Ensure the Efficient Circulation of Strategic Resources; ③ Promote; Promote Tariff Liberalization in Antimony Trade and Eliminate Market Access Barriers; ④ Strengthen the Government’s Strategic Support for the Antimony Industry to Enhance Global Discourse Power in Antimony Trade; Trade; ⑤ Maintain Macroeconomic Stability and Flexibly Manage Exchange Rates to Safeguard the Resilience of Antimony Trade. Full article

The global energy transition is expected to require three to twenty times more land areas than fossil fuel-based power generation, making the availability of suitable land for the global energy transition a key challenge. Based on different types of energy resources, this study designs a telecoupling multi-regional input–output (MRIO) model to analyze cross-border electricity-driven embodied land appropriation patterns. The results show that the land footprint associated with renewable energy is substantially lower than that associated with conventional power generation. However, the growth rate of this footprint is 2.18 times higher than that of conventional electricity generation. China and Germany are identified as key export markets for wind- and solar- driven embodied land. The share of electricity-driven embodied land from China to the United States, Japan, and Germany declined, whereas the embodied land flowing to countries including South Korea, India, and Singapore increased. Embodied land-exporting nations face trilemma issues related to environmental degradation chain reactions, resource consumption threshold lines, and social distribution tensions, which may significantly affect decarbonization progresses. By integrating renewable power infrastructures and land use occupation, this analytical framework is expected to advance the understanding of energy–land nexus dynamics, providing theoretical foundations for cross-system governance in the implementation of carbon neutrality. Full article