Search Results (77)

Economic stability in emerging market economies is increasingly shaped by the interplay between global financial integration, domestic monetary dynamics, and asset price fluctuations. Yet, early detection of financial market disruptions remains a persistent challenge. This study constructs a Financial Stress Index (FSI) for Pakistan, utilizing monthly data from 2005 to 2024, to capture systemic stress in a globalized context. Using Principal Component Analysis (PCA), the FSI consolidates diverse indicators, including banking sector fragility, exchange market pressure, stock market volatility, money market spread, external debt exposure, and trade finance conditions, into a single, interpretable measure of financial instability. The index is externally validated through comparisons with the U.S. STLFSI4, the Global Economic Policy Uncertainty (EPU) Index, the Geopolitical Risk (GPR) Index, and the OECD Composite Leading Indicator (CLI). The results confirm that Pakistan’s FSI responds meaningfully to both global and domestic shocks. It successfully captures major stress episodes, including the 2008 global financial crisis, the COVID-19 pandemic, and politically driven local disruptions. A key understanding is the index’s ability to distinguish between sudden global contagion and gradually emerging domestic vulnerabilities. Empirical results show that banking sector risk, followed by trade finance constraints and exchange rate volatility, are the leading contributors to systemic stress. Granger causality analysis reveals that financial stress has a significant impact on macroeconomic performance, particularly in terms of GDP growth and trade flows. These findings emphasize the importance of monitoring sector-specific vulnerabilities in an open economy like Pakistan. The FSI offers strong potential as an early warning system to support policy design and strengthen economic resilience. Future modifications may include incorporating real-time market-based metrics indicators to better align the index with global stress patterns. Full article

As a key tropospheric photochemical pollutant, ground-level ozone (O₃) poses significant threats to ecosystems through its strong oxidative capacity. With China’s rapid industrialization and urbanization, worsening O₃ pollution has emerged as a critical environmental concern. This study examines O₃’s impacts on forest ecosystems in Southwestern China (Yunnan, Guizhou, Sichuan, and Chongqing), which harbors crucial forest resources. We analyzed high-resolution monitoring data from over 200 stations (2019–2023), employing spatial interpolation to derive the regional maximum daily 8 h average O₃ (MDA8-O₃, ppb) and accumulated O₃ exposure over 40 ppb (AOT40) metrics. Through AOT40-based exposure–response modeling, we quantified the forest relative yield losses (RYL), economic losses (ECL) and ECL/GDP (GDP: gross domestic product) ratios in this region. Our findings reveal alarming O₃ increases across the region, with a mean annual MDA8-O₃ anomaly trend of 2.4% year⁻¹ (p < 0.05). Provincial MDA8-O₃ anomaly trends varied from 1.4% year⁻¹ (Yunnan, p = 0.059) to 4.3% year⁻¹ (Guizhou, p < 0.001). Strong correlations (r > 0.85) between annual RYL and annual MDA8-O₃ anomalies demonstrate the detrimental effects of O₃ on forest biomass. The RYL trajectory showed an initial decline during 2019–2020 and accelerated losses during 2020–2023, peaking at 13.8 ± 6.4% in 2023. Provincial variations showed a 5-year averaged RYL ranging from 7.10% (Chongqing) to 15.85% (Yunnan). O₃ exposure caused annual ECL/GDP averaging 4.44% for Southwestern China, with Yunnan suffering the most severe consequences (ECL/GDP averaging 8.20%, ECL averaging CNY 29.8 billion). These results suggest that O₃-driven forest degradation may intensify, potentially undermining the regional carbon sequestration capacity, highlighting the urgent need for policy interventions. We recommend enhanced monitoring networks and stricter control methods to address these challenges. Full article

This study investigates the impact of cultural openness on intertemporal consumption behavior in the Middle East and North Africa (MENA) region, using panel data from 14 countries spanning 2010 to 2022. Unlike prior research that primarily focused on lifestyle shifts or product preferences, this study explores how cultural globalization influences the trade-off between present consumption and future savings, as captured by the consumption-to-savings ratio (LCESR). Cultural openness is operationalized using the Cultural Globalization General Index (LCGGI), and its effect is analyzed alongside key control variables including Internet penetration, real GDP per capita, inflation, and tourism. To address endogeneity and unobserved heterogeneity, this study employs the system Generalized Method of Moments (GMM) estimator, supported by robustness check models. The findings reveal a significant positive relationship between cultural openness and LCESR in both the short and long run, indicating that increased exposure to global cultural flows enhances consumption tendencies in the region. Internet penetration and inflation negatively affect saving behavior, while GDP per capita shows a positive effect. Tourist arrivals exhibit limited influence. This study also highlights the importance of historical consumption behavior, as the lagged dependent variable strongly predicts the current LCESR. Robustness checks confirm the consistency of the results across all models. These insights suggest that cultural openness, digital infrastructure, and macroeconomic stability are pivotal in shaping consumption/saving patterns. The results carry important implications for financial education, digital consumption governance, and cultural policy strategies in the MENA region and similar emerging markets undergoing rapid cultural integration. Full article

Viticulture contributes significantly to Chile’s exports and GDP. However, the development and productivity of grapevines is threatened by climate change. Grapevines are grown in diverse regions; thus, adaptable tools for evaluating climate risk at the local level are required. In this study, a local climate risk index (LCRI) was developed to assess the vulnerability of Chilean viticulture (wine, table, and pisco grapes) in the current (2017–2024) and future (2046–2065) periods. Various components, including exposure, sensitivity, and adaptive and response capacities, were analyzed using different indicators based on municipal-level information. The results for the current period indicated that most municipalities were at medium risk, whereas future projections showed a marked increase in climate risk, principally due to changes in climate suitability. In the current period, the highest LCRI values were observed in semi-arid and mediterranean zones, particularly in the northern regions of Atacama and Coquimbo; in the future period, this situation intensified. In contrast, the lowest values in the current period occurred in the Maule region and further south, where the climate transitions from mediterranean to temperate conditions, and in the future period, valley and mountainous areas presented improvements in the index. Some municipalities showed improvement or stability with local adaptation efforts. The results highlight the urgent need for region-specific adaptation policies that prioritize water management, infrastructure, and increased capacities. Full article

During urbanisation, extensive production and construction activities encroach on ecological spaces, leading to changes in environmental structures and soil erosion. The issue of yellow muddy water caused by rainfall in cities with high construction intensity has garnered significant attention. Taking Guangzhou City as the research area, this study is the first to propose a risk assessment model for yellow muddy water in cities with high construction intensity, and the influence of construction sites on yellow muddy water was fully considered. Rainfall and construction sites were used as indicators to assess the hazards of yellow muddy water. Elevation, slope, normalised difference vegetation index (NDVI), soil erosion modulus, stream power index (SPI), surface permeability, and roads represent the exposure evaluation indicators. Population number and GDP (Gross Domestic Product) were used as vulnerability evaluation indicators. Based on the analytic hierarchy process (AHP) method, the weights of each evaluation indicator were determined, and a risk assessment system for yellow muddy water was established. By overlaying the weighted layers of different evaluation indicators on the geographic information system (GIS) platform, a risk degree distribution map of yellow muddy water disasters was generated. The evaluation results demonstrated that the disaster risk levels within the study area exhibited spatial differentiation, with areas of higher risk accounting for 14.76% of the total. The evaluation results were compared with historical yellow muddy water event information from Guangzhou, and the effectiveness of the model was verified by the receiver operating characteristic (ROC) curve. The validation results indicate that this model provides high accuracy in assessing the degree of risk of yellow muddy water in high-construction-intensity cities, offering effective technical support for precise disaster prevention and mitigation. Full article

As one of the major public health security issues, pulmonary tuberculosis had a global death rate of 1.6 million in 2021 alone, ranking 13th in the world, posing a great threat to society and families. Analyzing the temporal and spatial distribution and evolution trend of tuberculosis, discussing the exposure factors and studying the environmental background that affects the incidence can provide the basis for accurate prevention and control and promote the healthy and stable development of society. Based on the county scale, this study determined the high-incidence areas through hot spot analysis and selected nine districts and counties covering meteorological stations and air monitoring stations. The explanatory power of each factor to the incidence of pulmonary tuberculosis was analyzed by geographical detector, and the main influencing factors were explored. The results show that the following: (1) The number and incidence of pulmonary tuberculosis in Gansu Province declined from 2020 to 2022. (2) The influence of meteorological conditions such as temperature, precipitation and air pressure on pulmonary tuberculosis in different regions shows significant regional differences. Although the meteorological influence in adjacent regions shows certain convergence, the change in wind speed has no significant influence on the risk of pulmonary tuberculosis. (3) PM₁₀, altitude, temperature, population density and GDP per capita have strong explanatory power to the incidence of tuberculosis, and the interaction between any two factors exceeds the effect of a single factor in explanatory power, showing the characteristics of two-factor enhancement and nonlinear enhancement. Full article

Mounting evidence suggests an increasing heatwave risk in the Chinese mainland, posing notable threats to public health and the socioeconomic landscape. In a comprehensive analysis, considering both climate and socioeconomic factors, including Gross Domestic Product (GDP) and population dynamics, we systematically evaluated the spatiotemporal distribution of heatwave socioeconomic exposure in the Chinese mainland from 2000 to 2019, utilizing a more comprehensive heatwave hazard index (HHI) that synthesizes heatwave intensity, frequency, and duration as climate factor for the first time. Results show that (1) Heatwave exposure is pronounced in eastern China, particularly in Southeast (SE), North China (NC), and Southwest (SW) regions. From 2000 to 2019, heatwave exposure showed an overall upward trend, with the most rapid escalation observed in the SE, NC, and SW regions. Population exposure manifests as a clustered expansion pattern, while GDP exposure demonstrates a more centralized distribution. (2) Climatic factors exert the most notable influence on population exposure, while GDP predominantly impacts economic exposure. The combination of climate and socioeconomic factors contributes less to exposure rates, except in the Northeast (NE) and Southwest (SW) regions where it impacts GDP exposure most. (3) High-risk hotspot cities include Shanghai, Beijing, Chongqing, Guangzhou, Wuhan, Zhengzhou, Hangzhou, Xi’an, Tianjin, and Nanjing. These findings underscore the urgent need for targeted interventions and mitigation strategies in these vulnerable areas. Full article

Investigating changes in compound dry and hot events (CDHEs) and evaluating the associated socioeconomic exposure under climate change are critical for developing effective climate change mitigation and adaptation strategies. However, the socioeconomic exposure and the contributions of various driving factors to socioeconomic exposure under different warming levels remain poorly understood. Using the latest climate experiments from Coupled Model Intercomparison Project Phase 6 (CMIP6), this study assessed future changes in the frequency and socioeconomic exposure of CDHEs and explored the contributing drivers in the Yangtze River Basin (YRB) under 1.5 °C, 2.0 °C, and 3.0 °C global warming scenarios. Results indicate that the occurrences of CDHEs are projected to increase by 2.9, 3.9, and 4.8 times in a 1.5 °C, 2.0 °C, and 3.0 °C warmer world, respectively, compared to the present period (1985–2014). Population exposure to CDHEs increases significantly, with the greatest magnitude occurring at the 2 °C warming scenario. GDP exposure is expected to intensify continuously as the global average temperature rises, with the area experiencing significant increases continuously expanding. Climate change is the dominant driver of total projected changes in population exposure to CDHEs, accounting for approximately 105.6% at 1.5 °C, 110.3% at 2.0 °C, and 141.0% at 3.0 °C. At 1.5 °C, 2.0 °C, and 3.0 °C warming levels, changes in GDP exposure are primarily driven by the synergistic interaction between climate and GDP, accounting for 50.7%, 62.0%, and 64.8%, respectively. These findings provide valuable insights for climate change mitigation and adaptation strategies. Full article

Background: Quarantine is one of the most effective strategies to control outbreaks of communicable diseases. Individuals under isolation or quarantine experience both physical and mental effects. Therefore, given its widespread implementation around the world, it is pertinent to analyze this effect on physical and mental health. The psychosocial impact model, which divides four dimensions into two main points, exposure or protection and positive or negative responses, was used to analyze the psychosocial impact of quarantine. Objectives: The present study aimed to investigate the psychosocial impact of people exposed to or protected from quarantine. Methods: We conducted a search for primary articles in the Web of Science and Scopus databases, and after applying the inclusion and exclusion criteria, we meta-analyzed five of them. Results: Quarantined individuals were more likely to experience anxiety (K = 4; OR = 2.62) and depressive symptoms (K = 6; OR = 1.61) compared to those who did not undergo quarantine. Researchers discuss a twofold increase in the probability of anxiety or depression among those in quarantine. As a result, advancing interventions that reduce this impact is critical for both health and the global economy. Conclusions: In terms of economic variables, the non-moderation of GDP per capita and the moderation of the GINI index stand out, demonstrating that countries must move toward policies that promote the reconstruction of more resilient and inclusive societies. Full article

Compound extreme events can cause serious impacts on both the natural environment and human beings. This work aimed to explore the changes in compound drought–heatwave and heatwave–extreme precipitation events (i.e., CDHEs and CHPEs) across China using daily-scale gauge-based meteorological observations, and to examine their future projections and potential risks using the Coupled Model Intercomparison Project (CMIP6) under the shared socioeconomic pathway (SSP) scenarios (i.e., SSP1-2.6, SSP2-4.5, and SSP5-8.5). The results show the following: (1) The frequencies of CDHEs and CHPEs across China showed a significant increasing trend from 1961 to 2020, with contrasting trends between the first half and second half of the period (i.e., a decrease from 1961 to 1990 and an increase from 1991 to 2020). Similar trends were observed for four intensity levels (i.e., mild, moderate, severe, and extreme) of CDHEs and CHPEs. (2) All the frequencies under three SSP scenarios will show increasing trends, especially under higher emission scenarios. Moreover, the projected intensities of CDHEs and CHPEs will gradually increase, especially for higher levels. (3) The exposure of the population (POP) and Gross Domestic Product (GDP) will be concentrated mainly in China’s coastal areas. The GDP exposures to the CDHEs and CHPEs will reach their highest values for SSP5-8.5, while the POP exposure will peak for SSP2-4.5 and SSP5-8.5, respectively. Our findings can offer scientific and technological support to actively mitigate future climate change risks. Full article

China’s vulnerability to fluvial floods necessitates extensive exposure studies. Previous large-scale regional analyses often relied on a limited set of assessment indicators due to challenges in data acquisition, compounded by the scarcity of corresponding large-scale flood distribution data. The integration of public datasets offers a potential solution to these challenges. In this study, we obtained four key exposure indicators—population, built-up area (BA), road length (RL), and average gross domestic product (GDP)—and conducted an innovative analysis of their correlations both overall and locally. Utilising these indicators, we developed a comprehensive exposure index employing entropy-weighting and k-means clustering methods and assessed fluvial flood exposure across multiple return periods using fluvial flood maps. The datasets used for these indicators, as well as the flood maps, are primarily derived from remote sensing products. Our findings indicate a weak correlation between the various indicators at both global and local scales, underscoring the limitations of using singular indicators for a thorough exposure assessment. Notably, we observed a significant concentration of exposure and river flooding east of the Hu Line, particularly within the eastern coastal region. As flood return periods extended from 10 to 500 years, the extent of areas with flood depths exceeding 1 m expanded markedly, encompassing 2.24% of China’s territory. This expansion heightened flood risks across 15 administrative regions with varying exposure levels, particularly in Jiangsu (JS) and Shanghai (SH). This research provides a robust framework for understanding flood risk dynamics, advocating for resource allocation towards prevention and control in high-exposure, high-flood areas. Our findings establish a solid scientific foundation for effectively mitigating river flood risks in China and promoting sustainable development. Full article

Long-term exposure to PM_2.5 pollution increases the risk of cardiovascular diseases, particularly ischemic heart disease (IHD). Current assessments of the health effects related to PM_2.5 exposure are limited by sparse ground monitoring stations and applicable disease research cohorts, making accurate health effect evaluations challenging. Using satellite-observed aerosol optical depth (AOD) data and the XGBoost-PM25 model, we obtained 1 km scale PM_2.5 exposure levels across China. We quantified the premature mortality caused by PM_2.5-exposure-induced IHD using the Global Exposure Mortality Model (GEMM) and baseline mortality data. Furthermore, we employed the Gini coefficient, a measure from economics to quantify inequality, to evaluate the distribution differences in health impacts due to PM_2.5 exposure under varying socioeconomic conditions. The results indicate that PM_2.5 concentrations in China are higher in the central and eastern regions. From 2007 to 2022, the national overall level showed a decreasing trend, dropping from 47.41 μg/m³ to 25.16 μg/m³. The number of premature deaths attributable to PM_2.5 exposure increased from 819 thousand in 2007 to 870 thousand in 2022, with fluctuations in certain regions. This increase is linked to population growth and aging because PM_2.5 levels have decreased. The results also indicate disparities in premature mortality from IHD among different economic groups in China from 2007 to 2022, with middle-income groups having a higher cumulative proportion of IHD-related premature deaths compared with high- and low-income groups. Despite narrowing GDP gaps across regions from 2007 to 2022, IHD consistently “favored” the middle-income groups. The highest Gini coefficient was observed in the Northwest (0.035), and the lowest was in the South (0.019). Targeted policy interventions are essential to establish a more equitable atmospheric environment. Full article

The EU faces two economic challenges: managing non-performing exposures (NPEs) and climate change. This paper analyzes the relationship between the NPEs of domestic banking groups and climate risks, including macroeconomic variables such as the GDP growth rate, unemployment rate (UnEmp), and the voice and accountability percentile (VCA) and the interaction variable between the GHG and the Rule of Law Percentile (GhGRLP). The estimation uses ordinary least squares with time-fixed and individual effects. Physical and transition risks significantly affect NPEs, showing that both adverse climate events and the transition to a low-carbon economy worsen the financial situation of European banking institutions. The analysis also revealed that increased levels of VCA lead to a rise in NPEs, while an increase in GhGRLP reduces NPEs. In contrast, financial institutions tend to recognize and report NPEs more accurately in contexts with greater transparency and accountability. In comparison, UnEmp negatively affects NPEs, suggesting that economic support measures during high unemployment can reduce NPEs in the subsequent period. In conclusion, climate risk management represents a crucial challenge for the financial stability of banking institutions. Policymakers and financial institutions must continue to develop and implement climate change mitigation and adaptation strategies to preserve financial system stability amid growing climate uncertainties. Full article

Energy policy has a significant impact on the state of the environment and, therefore, on residents’ health and life expectancy, especially in highly urbanized areas. Reducing emissions is currently one of the necessary actions that must be taken at the scale of individual countries to ensure sustainable development. The article aims to identify the best ways to shape energy policy by evaluating development scenarios for air protection and their environmental impact. The realization of the goal is based on the data included in three groups: (1) Economic factors, Health factors, and Demographic factors; (2) Clima-e related economic losses, Renewable Energy sources in electricity, heating, and cooling, Premature deaths due to exposure to fine particulate matter (PM2.5), Health impacts of air pollution, Population change; (3) Demographic balance and crude rates at the national level, GDP per capita in purchasing power PPS, GDP, and principal components; covering 36 EU countries in 2019 and 2021. The study proposes an advanced methodology for assessing development strategies by integrating the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Bayesian networks (BN) and incorporating them into a multicriteria decision-making (MCDM) support system. The TOPSIS model based on BN allowed for the illustration of the features of many criteria and the identification of relationships between scenarios, allowing for selecting the best way to develop energy policy. The results showed a 60.39% chance of achieving success in extending the life of residents by five years. At the same time, the most favorable development path was the scenario promoting activities aimed at reducing air pollution by introducing renewable energy sources to produce energy used for lighting and preparing domestic hot water urban areas. By presenting possible scenarios and the probability of success, it is possible to achieve the goal of practical energy policy at the level of the country and individual European cities and also by extending the life of city inhabitants, as presented by the authors in this study. Full article

The impending challenge posed by escalating heatwave events due to projected global warming scenarios of 1.5 and 2.0 °C underscores the critical need for a comprehensive understanding of their impact on human health and socio-economic realms. This study delves into the anticipated implications of elevated global temperatures, specifically the 1.5 and 2.0 °C warming scenarios under the SSP2-4.5 and SSP5-8.5 pathways, on population and GDP exposure to heatwaves in China. We also evaluated the aggregated impacts of climate, population, and GDP and their interactions on future socio-economic exposure across China. We leveraged data sourced from the climatic output of Coupled Model Intercomparison Project Phase 6 (CMIP6) for heatwave analysis and integrated population and GDP projections under divergent Shared Socio-economic Pathways (SSPs), including SSP2-4.5 (low emission) and SSP5-8.5 (high-emission). Results indicate a drastic surge in the number of heatwave days under both warming scenarios, particularly in regions like Xinjiang (XJ), North China (NC), and South China (SC) subregions, with a notable disparity in the elevation of heatwave days among different levels. There is an alarming surge in population exposure, escalating approximately 7.94–8.70 times under the 1.5 °C warming scenario and markedly increasing by 14.48–14.75 times by the 2100s relative to the baseline (1985–2014) under the more extreme 2.0 °C warming level. Likewise, the study unveils a substantial elevation in GDP exposure, ranging from 40.65 to 47.21 times under the 1.5 °C warming level and surging dramatically by 110.85–113.99 times under the 2.0 °C warming level. Further analyses disclose that the climate effect predominantly influences changes in population exposure, constituting 72.55–79.10% of the total change. Meanwhile, the interaction effect notably shapes GDP exposure alterations, contributing 77.70–85.99% to the total change. The comprehensive investigation into alterations in population and GDP exposure under varying warming scenarios, coupled with the quantification of each contributing factor, holds paramount importance in mitigating the detrimental repercussions of heatwaves on both human life and socio-economic landscapes. Full article