Search Results (581)

The urban heat island (UHI) effect represents a critical urban climate phenomenon arising from the combined pressures of rapid urbanization and climate warming. Although its association with carbon emissions has received increasing scholarly attention, the underlying behavior-mediated pathways and cross-regional spillover patterns remain insufficiently understood. Using multi-source geospatial data for the Yangtze River Delta urban agglomeration from 2014 to 2023, this study develops a multi-scale analytical framework integrating 1 km urban agglomeration exploratory analysis and 5 km spatial econometric modeling. Anthropogenic Energy Activity Intensity (AEAI) is constructed as a proxy for energy-related human activities, and a spatial Durbin model, combined with a spatial mediation approach, is employed to examine the spatial associations and statistically mediated pathways within the “heat-energy-carbon” nexus. The results indicate that: (1) carbon emissions exhibit significant positive spatial spillover effects, consistent with thermal diffusion processes and socioeconomic network interactions; (2) AEAI represents a substantial partial statistical mediation pathway in the association between UHI and carbon emissions, accounting for 44.63% of the total association. This suggests that the UHI–carbon emission linkage is partly embedded in spatial patterns of energy-intensive human activities rather than reflecting a purely direct thermal effect. These findings suggest that regional climate governance may need to move beyond single-city interventions and purely physical cooling strategies toward integrated approaches that combine cross-regional coordination with behavioral regulation. Promoting passive cooling-oriented urban planning and demand-side energy transitions may help reduce carbon lock-in risks and support the development of climate-resilient urban agglomerations. Full article

This study synthesises evidence on whether, why, and under what conditions digital technologies improve resource efficiency across multi-tier global value chains (GVCs) and examines the theoretical adequacy of dominant explanatory lenses. Following the PRISMA 2020 protocol, we searched Web of Science, Scopus, IEEE Xplore, and ProQuest, retaining 150 articles for qualitative synthesis and 137 for bibliometric science-mapping; themes were developed via multi-cycle coding and triangulated with co-citation and keyword co-occurrence networks. Reported efficiency gains are strongest when firms deploy integrated digital stacks combining IoT sensing, AI analytics, blockchain traceability, and digital twins that jointly enable visibility, verification, and simulation-based optimisation, a pattern based predominantly on observational and cross-sectional evidence. Outcomes are contingent on cross-firm capability complementarities, data-governance arrangements, regulatory congruence, and cyber-risk maturity. A key structural finding is the digital-regionalisation paradox: stringent data-compliance demands can re-anchor sourcing within regulatory blocs, concentrating rather than extending GVC geography. Building on these findings, we propose three theoretical extensions, namely ecosystemic capability bundling, digital-sustainability spillovers, and distributed eco-innovation, that advance Transaction Cost Economics, the Resource-Based View, Dynamic Capabilities, and GVC governance theories to better account for the sustainability and platform dimensions of contemporary digitalised value chains. Full article

Bats (Chiroptera) account for approximately 25% of all known mammalian species and provide essential ecological services, including insect regulation, pollination, and seed dispersal. Despite their importance, they face significant conservation threats and persistently negative social perceptions. Owing to their innate immunity and tolerance, bats constitute a particularly efficient natural reservoir for a wide variety of potentially zoonotic viruses. Over the past two decades, bat-associated viruses have been central to multiple outbreaks of emerging infectious diseases. From severe acute respiratory syndromes to filoviral hemorrhagic fevers, bats have consistently acted as key reservoirs in pathogen emergence. This has further damaged the public perception of bats as dangerous animals and vectors of serious diseases, in some cases leading to increased persecution of their populations. However, spillover events should not be attributed to bats, but rather to human-driven environmental changes—including deforestation, land-use transformation, agricultural intensification, urban expansion, biodiversity loss, wildlife trade and research biosecurity—that amplify contact among humans, livestock, and wildlife or their potential zoonotic pathogens. Safeguarding bat populations, minimizing direct interactions with wildlife, and preserving intact ecosystems are critical not only for bat conservation but also for reducing zoonotic spillover risk. Furthermore, it is essential to strengthen social communication regarding the importance of bats, in order to counteract their negative reputation and promote greater public understanding of their ecological value. This article reviews health, sociological, and conservation dimensions of the issue, situating them within a broader context to provide an integrated, multidisciplinary understanding. Potential solutions and priority directions for future research are also discussed. Full article

This study investigates whether the March 2023 failure of Silicon Valley Bank (SVB) coincided with changes in market-risk exposure, abnormal returns, and return connectedness among five major Chinese financial institutions. Using daily data from January 2022 to December 2023, we apply CAPM and market-model regressions, structural-break tests, event-study methods, and generalized forecast-error variance decompositions. The revised design distinguishes 10 March from the first subsequent Chinese trading day, 13 March, and adds symmetric event windows, placebo tests, an alternative risk-free rate, return-series audits, significance tests, and VAR diagnostics. Full-sample Chow tests identify breaks for ICBC and CITIC Securities, but only ICBC remains significant within the ±60-day window, and none are significant within ±30 days. Only ICBC records a significant positive CAR over [−3, +3]. Overall connectedness falls from 55.53% to 47.98%, while CITIC Securities becomes the largest post-event net transmitter. The evidence therefore indicates selective repricing and reconfigured linkages rather than a system-wide effect, and does not support unique causal attribution to SVB. Full article

Forecasting multi-asset volatility spillovers and turning the forecasts into risk-aware portfolios requires methods that uncover directional information flow between assets, compress the state into a minimal sufficient representation, deliver calibrated uncertainty, and respect explicit tail-risk limits. We propose TDV (Transfer-entropy, Dynamic-graph-attention, Variational-information-bottleneck), an information-theoretic artificial intelligence framework that couples a time-varying transfer entropy network with a graph attention encoder regularised by a variational information bottleneck, and demonstrates the practical value of the calibrated predictive distribution through a downstream entropy-regulated, CVaR-constrained portfolio application. We establish three theoretical results: $L^2$ consistency of the k-nearest-neighbour transfer entropy estimator on $\alpha$-mixing returns with rate $O_P\left(n^{-2/(2+d)}\right)$, a PAC–Bayes generalisation bound of order $O\left(\sqrt{\left(I\right(X;Z)+log(1/\delta \left)\right)/n}\right)$ for the bottleneck-encoded forecaster, and asymptotic CVaR feasibility of the plug-in allocation. In simulations across sparse Granger networks, contagion DCC–GARCH ensembles, and regime-switching factor models, the framework cuts spillover forecasting errors by 24 to 42 percent against LSTM, vanilla GAT, and Transformer baselines, and it recovers 1.6 additional nats of mutual information with the realised connectedness matrix. On a 32-asset global panel covering 2014 to 2025, the model delivers an out-of-sample $R^2$ of 0.331, an annualised Sharpe ratio of 1.46 against 0.83 for an equally weighted benchmark, a maximum drawdown of 7.8 percent, and 95 percent CVaR reductions of 28 to 36 percent across sub-periods relative to a shrinkage minimum-variance baseline. Full article

This paper examines whether quantile-based connectedness measures contain useful information for portfolio risk management. Using U.S. sector equity data, we estimate connectedness measures within a quantile vector autoregression framework and construct portfolios based on the cross-sectional distribution of net connectedness. In particular, sectors identified as extreme shock transmitters receive lower portfolio weights. Our results reveal substantial asymmetries across quantiles. Portfolios constructed using lower-tail connectedness measures exhibit smaller maximum drawdowns and lower expected shortfall relative to both equal-weight benchmarks and portfolios based on upper-tail connectedness. By contrast, median connectedness measures tend to provide more stable overall portfolio performance and lower turnover. The findings also suggest that the informational content of connectedness depends critically on the quantile considered. Lower-tail connectedness becomes particularly informative during crisis periods, suggesting that downside spillovers play an important role in portfolio resilience and systemic risk transmission. Overall, the results demonstrate that quantile connectedness measures provide economically meaningful information for downside risk management and offer a simple and transparent framework for incorporating systemic risk into portfolio construction. Full article

Sustainable air-quality governance requires not only local emission reduction but also a shift from single-pollutant control to coordinated PM_2.5–O₃ control, and from city-bounded management to regional governance under spatial spillovers. Based on balanced annual city-level panel data for the “2 + 26” urban agglomeration in the Beijing–Tianjin–Hebei region and surrounding areas from 2013 to 2020, this paper uses the dynamic Spatial Durbin Model (SDM) to analyze the spatial spillover effect of PM_2.5 and O₃ pollution and the effect of regional governance policies. The results show that both PM_2.5 and O₃ exhibit significant spatial autocorrelation and cross-city dependence, indicating that isolated local control measures are insufficient for sustainable air pollution prevention and that city-bounded governance cannot fully address regionally connected pollution risks. Economic output and secondary-industry employment remain important structural factors of pollution. The policy-text analysis shows that measures centered on coal-related control and industrial governance were more directly aligned with PM_2.5 reduction, whereas O₃-related governance lagged, suggesting that single-pollutant-oriented control may generate a sustainability trade-off when PM_2.5 reduction is not accompanied by coordinated O₃ control. These findings highlight two sustainability challenges in China’s regional air-quality governance: first, single-pollutant control can improve particulate pollution but may not ensure sustainable air-quality improvement when O₃ and its precursors are insufficiently addressed; second, isolated city-level governance may be insufficient when pollution outcomes exhibit significant spatial dependence across administrative boundaries. The study provides empirical evidence for sustainable air-quality governance by emphasizing differentiated PM_2.5 and O₃ responses, coordinated PM_2.5–O₃ control, regional governance beyond individual city boundaries, and the integration of spatial spillover assessment into regional environmental policy design. Full article

This study investigates the transmission of global risk sentiment and U.S. monetary conditions across emerging equity markets. Using Multiple Wavelet Coherence (MWC) and Quantile-on-Quantile Regression (QQR) over January 2016–December 2025, the analysis examines time–frequency co-movements and asymmetric linkages between emerging market equity indices, the CBOE Volatility Index (VIX), and the U.S. Treasury yield spread (T10Y3M). The results reveal substantial heterogeneity across markets. China, Russia, Turkey, Mexico, Egypt, and South Africa exhibit stronger long-run synchronization with external financial conditions. Saudi Arabia and Nigeria display more episodic exposure to external shocks. India, Brazil, Indonesia, and the United Arab Emirates represent intermediate cases characterized by recurrent but less persistent linkages. The findings suggest that global risk sentiment and U.S. monetary conditions affect emerging markets differently across investment horizons and periods of financial stress. The robustness analysis indicates that synchronization patterns became fragmented following the tightening cycle and rising geopolitical tensions after 2022, with less uniform spillover transmission across regions. The analysis highlights the importance of nonlinear and time-varying mechanisms in shaping financial spillovers across emerging equity markets. Full article

Under the “dual carbon” targets, using green finance to support renewable energy use is an important way to reduce extreme climate risks. This study builds a balanced panel dataset of 271 Chinese cities from 2010 to 2021. We measured the level of Green Finance (GF) and renewable energy utilization (RE). Employing two-way fixed effects, the Spatial Durbin Model (SDM), and the Heterogeneous Spatial Autoregressive (HSAR) model, we systematically examine the promoting effects, transmission mechanisms, spatial heterogeneity, and economic–environmental consequences of GF on RE. The empirical results reveal that GF significantly enhances RE and generates pronounced positive spatial spillovers. Mechanism analysis indicates that R&D investment and environmental regulation serve as the primary transmission channels. The promotion effect is more pronounced in the eastern and central regions, as well as in areas with higher R&D investment and stricter environmental regulation, whereas the spatial spillover effect is particularly evident in coastal regions. Further consequence analysis demonstrates that GF contributes to reducing conventional energy intensity, improving green total factor productivity, and alleviating extreme climate events. Building on these findings, this study proposes spatially differentiated and sustainability-oriented policy strategies to advance China’s energy transition and foster coordinated economic and environmental sustainability. Full article

This paper studies the informational hierarchy of individual stocks in the Colombian Stock Exchange (BVC), with particular attention to the role of cross-listed securities. The paper addresses a gap in the literature on small emerging markets, where evidence on intra-market information and return transmission remains scarce, particularly in the presence of illiquidity, cross-listing, and external risk exposure. Using daily data for 2015–2024, we estimate a five-asset vector autoregression VAR (3) with exogenous global controls and compute generalized forecast error variance decompositions within the Diebold–Yilmaz connectedness framework, with residual-bootstrap inference and CBOE Volatility Index (VIX)-based regime analysis. The VIX regimes are used to distinguish low-, medium-, and high-global-risk environments because global risk appetite is a key channel through which external shocks affect emerging equity markets. Three results stand out. First, total connectedness is moderate in the full sample, at 25.2%, but rises sharply with global risk, from 17.5% in low-VIX periods to 28.4% in high-VIX periods. Second, Ecopetrol’s American Depositary Receipt listed on the New York Stock Exchange (EC, NYSE) emerges as the dominant net transmitter of return innovations, and its informational leadership becomes stronger as global uncertainty increases. Third, when the local Ecopetrol share is excluded, leadership shifts to Bancolombia’s ADR (CIB), suggesting that directional spillover leadership is associated not only with firm identity but also with the offshore trading venue. These findings document a regime-dependent and venue-driven informational hierarchy, consistent with ADR-listed securities acting as dominant transmitters of return innovations to the domestic Colombian equity system. For portfolio managers, the results imply that diversification across local Colombian equities may overstate the number of independent information sources, especially during high-risk periods, and that monitoring ADRs, global volatility, oil prices, and exchange-rate conditions may improve hedging and risk management. Full article

Using a dataset covering January 1975 to March 2026 and six agricultural commodities, wheat, corn, soybeans, oats, sugar, and coffee, this paper explores the role of geopolitical risk (acts and threats) in shaping cross-market connectedness. It proposes a multilayer methodology based on the time-varying parameter vector autoregressive (TVP-VAR), the exponential GARCH with exogenous variables (EGARCH-X), and the wavelet quantile correlation (WQC) frameworks. This methodology captures cross-market volatility spillovers, assesses the effects of geopolitical risk and its components on the strength and instability of connectedness, and incorporates nonlinearity and asymmetry across investment horizons and market conditions. The results show a time-varying pattern in agricultural cross-market connectedness. Corn and soybeans transmit volatility shocks, while the other commodities are net receivers. These commodities have a central position in the connectivity network, whereas sugar and coffee are in the peripheral zone. The EGARCH-X results show that geopolitical acts and threats do not significantly alter the overall level of connectedness but intensify its volatility, suggesting that geopolitical tensions primarily influence stability rather than the intensity of connectedness. Economic policy uncertainty and oil price volatility have similar effects. In line with these results, the WQC analysis uncovers significant nonlinearity and state-dependent linkages, underscoring that the effect of geopolitical acts and threats becomes prominent over medium- and long-term horizons and during periods of market stress. These findings contribute to the literature by differentiating the effects of geopolitical incidents on agricultural market connectedness versus volatility. From an operational standpoint, these results imply that policymakers and market operators should enhance their risk-monitoring and hedging strategies during periods of high geopolitical stress, as such events can amplify instability across agricultural commodity markets. Full article

Orthohantaviruses are zoonotic pathogens belonging to the family Hantaviridae and are responsible for significant human disease. These infections are characterized by acute systemic illness, vascular dysfunction, and, in severe cases, hemorrhage and multiorgan failure. Depending on the viral species involved, infection may result in hemorrhagic fever with renal syndrome (HFRS) or hantavirus cardiopulmonary syndrome (HCPS), both of which are associated with substantial morbidity and mortality. Rodents act as natural reservoirs, maintaining viral persistence in endemic ecosystems and enabling sporadic spillover to humans through exposure to infected excreta or contaminated environments. This review synthesizes current knowledge on rodent reservoir competence, hantavirus replication strategies, pathogenesis, clinical manifestations, ecological drivers of transmission, public health implications and future therapeutic developments and challenges. Understanding these mechanisms is essential for enhancing surveillance, risk assessment, and preventive strategies against orthohantavirus infections. Full article

To systematically examine the impact of climate risks on China’s financial system, this study employs the EGARCH-SGED model to precisely fit financial market volatility based on China’s Climate Change News Index. It then combines the LASSO-CoVaR method to measure tail risk spillover effects within China’s financial system under climate risk shocks, constructs a risk contagion network, and innovatively utilizes the RF-AdaBoost model to establish the risk early warning system. Findings reveal that climate risk is a key driver of dynamic correlation evolution within the financial system, with heterogeneous impacts across different markets. Physical climate risk events intensify short-term risk contagion while generating long-term effects; transition risks undergo a dynamic process, initially amplifying uncertainty before enhancing systemic stability over the long term. The RF-AdaBoost model outperforms traditional machine learning models in risk warning, demonstrating outstanding predictive accuracy and generalization capabilities, thereby providing effective intellectual support for climate risk prevention and financial stability management. Full article

The study investigates the relationship between political signal quality, uncertainty measures, and sovereign CDS connectedness among major oil-exporting countries using a time-varying parameter vector autoregressive (TVP-VAR) approach along with regression and quantile-based techniques. The findings indicate a moderate degree of sovereign connectedness, suggesting the presence of cross-country spillover effects in sovereign risk markets. The results further show that Qindex is negatively associated with sovereign connectedness both in the case of normal market conditions and mild stress levels. In contrast, conventional uncertainty indicators appear to exert relatively weaker effects across model specifications. Overall, the findings suggest that the informational quality of political communication may play a role in shaping sovereign spillover dynamics alongside broader macroeconomic and financial conditions. Full article

Cross-market risk transmission in U.S. energy markets has become increasingly complex as fossil fuel prices, electricity markets, and clean energy financial exposure respond differently to stress episodes. Identifying whether dynamic spillover information contains forward-looking diagnostic value is therefore important for energy market risk monitoring. This study examines a daily six-market U.S. energy return panel covering WTI crude oil, Henry Hub natural gas, Brent crude oil, RBOB gasoline, PJM West electricity, and CELS clean-energy equity exposure from 2016 to 2025. We first estimate time-varying total, directional, and net connectedness using a TVP-VAR-DY framework and then transform the resulting connectedness measures into spillover-based features for supervised high-DSV20-state classification. The results show that energy-market connectedness is clearly time-varying, with crude oil benchmarks occupying central positions and market-level net spillover roles changing across market conditions. Under the retained label-80 Random Forest specification, connectedness-based features provide moderate diagnostic value for identifying future high-DSV20 states. Net WTI, Net Henry Hub, and Net CELS are the most informative spillover-role variables. Additional validation checks indicate that the evidence is best interpreted as support for diagnostic risk monitoring rather than as a high-accuracy forecasting system. The findings highlight the usefulness of dynamic connectedness measures as transparent inputs for energy-market risk assessment. Full article