Search Results (94)

Approximately 27.6% of Italian beaches are currently affected by erosion, despite the widespread implementation of coastal defence structures. Around 10,500 installations—mainly groins and detached breakwaters—occupy nearly 24.6% of the national shoreline. Although primarily designed to protect tourist beaches, these hard-engineered structures often degrade coastal landscapes, alter nearshore circulation, and pose risks to swimmers. Nevertheless, beaches remain a fundamental asset for the “3S” (Sun, Sea, Sand) tourism sector, which contributes approximately 2.2% to Italy’s GDP, accounting for over 175 million tourists’ overnight stays in 2024, frequently concentrated near protected coastal zones. In this study, drowning incidents along the Italian coastline were analyzed using press reports complemented by official statistics. Between 2016 and 2021, an average of 145 fatalities occurred per bathing season. Sudden drownings following medical emergencies accounted for 41% of cases, non-swimmers for 18%, accidental falls into the water for 3%, and water sports activities for an additional 3%. Rip currents on natural beaches were responsible for 22% of drownings, whereas those generated by coastal defence structures accounted for 12%. A further 12% of non-swimmer fatalities are suspected to have resulted from falls into depressions or channels formed in proximity to these structures. Evidence from previous studies and seabed morphology analyses indicates that coastal defence structures can generate rip currents through two main mechanisms: (1) hydraulic pressure exerted against groins, which drives offshore flow, and (2) water outflow between pairs of breakwaters resulting from wave setup behind them. Both processes, though often less intense, are also observed near submerged structures. The erosional channels formed by these currents may persist well beyond storm events, maintaining dangerous conditions for bathers. As Italy continues to rely predominantly on hard coastal protection measures, improving the understanding of drowning dynamics associated with these structures is crucial. This should be accompanied by regulatory updates requiring designers and coastal managers to systematically assess related hazards and to propose effective mitigation and safety strategies. Full article

Under the dual pressures of climate change and rapid urbanization, extreme heat events pose growing risks to densely populated megaregions. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA), a densely populated and economically vital region, serves as a critical hotspot for heat risk aggregation. This study develops a high-resolution multi-dimensional framework to assess the spatiotemporal evolution of its heat risk profile from 2000 to 2020. A Heat Risk Index (HRI) integrating heat hazard and vulnerability components to measure potential heat-related impacts is calculated as the product of the Heat Hazard Index (HHI) and Heat Vulnerability Index (HVI) for 1 km grids in GBA. The HHI integrates the frequency of hot days and hot nights. HVI incorporates population density, GDP, remote-sensing nighttime light data, and MODIS-based landscape indicators (e.g., NDVI, NDWI, and NDBI), with weights determined objectively using the static Entropy Weight Method to ensure spatiotemporal comparability. The findings reveal an escalation of heat risk, expanding at an average rate of 342 km² per year (p = 0.008), with the proportion of areas classified as high-risk or above increasing from 21.8% in 2000 to 33.3% in 2020. This trend was characterized by (a) a pronounced asymmetric warming pattern, with nighttime temperatures rising more rapidly than daytime temperatures; (b) high vulnerability dominated by the concentration of population and economic assets, as indicated by high EWM-based weights; and (c) isolated high-risk hotspots (Guangzhou and Hong Kong) in 2000, which have expanded into a high-risk belt across the Pearl River Delta’s industrial heartland, like Foshan seeing their high-risk area expand from 3.4% to 27.0%. By combining remote sensing and socioeconomic data, this study provides a transferable framework that moves beyond coarse-scale assessments to identify specific intra-regional risk hotspots. The resulting high-resolution risk maps offer a quantitative foundation for developing spatially explicit climate adaptation strategies in the GBA and other rapidly urbanizing megaregions. Full article

Traffic accidents remain a major global burden, causing mortality, disability, and socio-economic losses that hinder sustainable development. Beyond human suffering, crashes place long-term pressures on health systems, labor markets, and national economies, disproportionately impacting low- and middle-income countries. Estimating the true societal costs of accidents is therefore essential for designing effective, equitable, and sustainable road safety policies. This study applies the Willingness-to-Pay (WTP) method to evaluate the external costs of traffic-related deaths and injuries in Türkiye between 2008 and 2018. By incorporating material and immaterial losses, the WTP framework captures a broader spectrum of impacts than traditional approaches, offering valuable insights into the scale of welfare losses and the value of risk reduction. The findings reveal that external costs rose substantially over the decade, from 1.63% to 2.72% of national Gross Domestic Product (GDP), underscoring that economic losses from road crashes are growing faster than the economy. These results highlight the need for systematic interventions that integrate road safety into national sustainability agendas, including safer infrastructure, behavioral programs, advanced vehicle technologies, and efficient emergency response systems. The evidence presented strengthens the case for prioritizing traffic safety as a fundamental component of sustainable transport and public health strategies. Full article

This study investigates the relationship between economic growth and environmental performance in selected Middle East and North Africa (MENA) countries through the lens of the Environmental Kuznets Curve (EKC) hypothesis. Due to data availability constraints, our sample includes Algeria, Egypt, Lebanon, Mauritius, Morocco, and Oman, covering the period 1990–2022. Using annual panel data, we apply panel cointegration techniques alongside Fully Modified Ordinary Least Squares (FMOLS) and Dynamic Ordinary Least Squares (DOLS) estimators, complemented by Granger causality tests, to examine the interaction among GDP per capita, renewable energy consumption, and transport service exports in determining CO₂ emissions per unit of GDP. The empirical findings provide only partial support for the EKC: while the DOLS results confirm an inverted U-shaped income–emissions relationship, the FMOLS estimations contradict it, suggesting a more complex and nonlinear pattern. Beyond testing the EKC, this study contributes two novel dimensions to the literature. First, it shows that renewable energy exerts a statistically significant negative effect on carbon intensity in the long run, despite weak short-run causality, highlighting the delayed but durable environmental benefits of clean energy adoption. Second, it introduces transport service exports as a proxy for structural economic transformation, capturing the role of trade-driven diversification in reducing emissions. By embedding renewable energy deployment and service-based trade dynamics into the EKC framework, the study advances a more policy-relevant and region-specific understanding of the growth–environment nexus in the selected MENA economies. The results underscore the importance of scaling renewable energy, promoting low-carbon service sectors, and aligning trade and environmental policies to ensure that economic growth supports long-term climate objectives. Full article

Aboveground biomass (AGB) is a key indicator of forest structure and carbon sequestration, yet its dynamics under concurrent anthropogenic disturbances remain poorly understood. This study investigates the spatiotemporal dynamics and driving mechanisms of AGB in the Jianfengling tropical lowland rainforest (JFLTLR) within Hainan Tropical Rainforest National Park (NRHTR) from 2015 to 2023. Six machine learning models—Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Support Vector Machine (SVM), k-Nearest Neighbors (KNN), Decision Tree (DT), and Random Forest (RF)—were evaluated, with RF achieving the highest accuracy (R² = 0.83). Therefore, RF was employed to generate high-resolution annual AGB maps based on Sentinel-1/2 data fusion, field surveys, socio-economic indicators, and topographic variables. Human pressure was quantified using the Human Influence Index (HII). Threshold analysis revealed a critical breakpoint at ΔHII ≈ 0.1712: below this level, AGB remained relatively stable, whereas beyond it, biomass declined sharply (≈−2.65 mg·ha⁻¹ per 0.01 ΔHII). Partial least squares structural equation modeling (PLS-SEM) identified plantation forests as the dominant negative driver, while GDP (−0.91) and road (−1.04) exerted strong indirect effects through HII, peaking in 2019 before weakening under ecological restoration policies. Spatially, biomass remained resilient within central core zones but declined in peripheral regions associated with road expansion. Temporally, AGB exhibited a trajectory of decline, partial recovery, and renewed loss, resulting in a net reduction of ≈ 0.0393 × 10⁶ mg. These findings underscore the urgent need for a “core stabilization–peripheral containment” strategy integrating disturbance early-warning systems, transportation planning that minimizes impacts on high-AGB corridors, and the strengthening of ecological corridors to maintain carbon-sink capacity and guide differentiated rainforest conservation. Full article

This paper estimates a nonlinear asymmetric dynamics model in the threshold panel data framework to study the extent to which the quality of governance, investment, and financial stability affect the impact of external debt on economic growth in 47 African countries from 2002 to 2022. As a general approach, we use the first-differenced GMM estimator, which allows both threshold variables and regressors to be endogenous. The results confirm that external debt becomes a drag on growth beyond a threshold of 53.49% relative to GDP. Furthermore, the results show that external debt appears to stimulate economic growth mainly by orienting it towards productive investment. In addition, the results show that better governance quality and financial stability accentuate the positive impact of external debt on economic growth. Based on the findings, this study proposes several policy recommendations. Full article

Saudi Arabia’s Vision 2030, unveiled by Crown Prince Mohammed bin Salman on 25 April 2016, aims to diversify the economy beyond oil dependency and engender robust foreign direct investment (FDI). This research investigates the primary economic challenges impeding foreign investors from entering the Saudi market and devises effective strategies to sustain FDI inflows. The study employs a comprehensive methodology, including an extensive literature review spanning from 2016 to 2023, supported by quantitative statistical analysis using a Multiple Linear Regression Model and qualitative insights derived from Delphi interviews with industry experts. The study’s outcomes reveal a significant disparity between the targeted FDI growth from 3.8% to 5.7% of GDP and the existing trajectory, highlighting pressing economic challenges that require immediate attention. Key findings indicate that factors such as population growth, government spending, and trade openness significantly influence FDI dynamics, with a particular emphasis on the positive impact of investment protection agreements. The integration of qualitative methodologies further elucidates the importance of robust legal frameworks and regulatory reforms in fostering an investor-friendly environment. Overall, this research provides strategic recommendations for improving the investment landscape in Saudi Arabia, aligning with the broader goals of Vision 2030, and enhancing the country’s attractiveness as a global investment destination. The commitment to fostering a conducive investment ecosystem serves as a pivotal mechanism for driving economic growth and achieving sustainable development goals within the Kingdom. Full article

RAC3 encodes a small Rho-family GTPase essential for cytoskeletal regulation and neurodevelopment, and de novo RAC3 variants typically act as gain-of-function alleles that cause severe neurodevelopmental disorders. In this study, we analyzed a fetus with multisystem congenital anomalies and identified a de novo RAC3 p.(T17R) variant by genome sequencing. To elucidate the pathogenicity of this variant, we combined in silico variant prioritization, structural and energetic modeling, and pathogenicity prediction with in vitro biochemical assays, including GDP/GTP exchange, GTP hydrolysis, effector pull-down, and luciferase reporter analyses in COS7 cells, as well as morphological analysis of primary hippocampal neurons. Furthermore, we performed in vivo analyses using a mouse in utero electroporation to assess cortical neuron migration, axon extension, and dendritic development. Our biochemical results suggest that RAC3-T17R exhibits markedly increased GDP/GTP exchange, with a preference for GDP binding, and undetectable GTP hydrolysis. The mutant displayed minimal binding to canonical RAC effectors (PAK1, MLK2, and N-WASP) and failed to activate SRF-, NFκB-, or AP1-dependent transcription. Neuronal overexpression of RAC3-T17R impaired axon formation in vitro, while in vivo expression delayed cortical neuron migration and axon extension and reduced dendritic arborization. Clinically, the fetus exhibited corpus callosum agenesis, microcephaly, organomegaly, and limb contractures. Collectively, these findings indicate that the RAC3 p.(T17R) variant may represent a signaling-deficient allele with pleiotropic, variant-specific mechanisms that disrupt corticogenesis and broader organogenesis. Our multi-tiered in silico–in vitro–in vivo approach demonstrates that noncanonical RAC3 variants can produce complex, multisystem developmental phenotypes beyond previously recognized RAC3-related neurodevelopmental disorders. Full article

Background/Objectives: The study proposes an indicator-based framework for monitoring health inequalities in Greece by examining key socioeconomic and health-related determinants. Methods: The framework draws on the World Health Organization’s Social Determinants of Health model and the Dahlgren–Whitehead model, using Eurostat data (2008–2023). Results: Life expectancy at birth showed a moderate negative correlation with public health expenditures (r = −0.716), while healthy life years were positively linked with GDP (r = 0.765) and public health expenditures (r = 0.743). Self-perceived health was strongly negatively correlated with poverty risk (r = −0.864). Chronic conditions and functional limitations were inversely associated with GDP and health spending. Social factors also mattered: healthy life years correlated negatively with unemployment (r = −0.814) and positively with employment (r = 0.810). Educational attainment influenced both self-perceived health and reported health problems. Conclusions: This framework goes beyond existing WHO/EU models by systematically integrating economic, social, and health outcome indicators tailored to the Greek context. It provides a comprehensive view of the determinants impacting health in Greece, enabling policymakers to tackle the underlying causes of health inequalities and enhance both the fairness and efficiency of healthcare services. Strengthening primary healthcare is crucial to reducing unmet medical needs, minimizing private health expenditures, and improving overall public health. Full article

Moving beyond Gross Domestic Product (GDP) as the sole measure of economic performance is increasingly critical for addressing the complex challenges of sustainable development. The Inclusive Wealth Index (IWI) offers a more comprehensive framework for assessing long-term sustainability by accounting for changes in produced, human, and natural capital. This paper contributes to this debate by examining the comparative dynamics of these three forms of capital in Greece in relation to European Union averages. Specifically, we employ a repeated-measures design and the mixed ANOVA method to analyse their interactions over time (1990–2020) and across regional contexts. The novelty is to cover the research gap on how the different capitals interact, with Greece serving as a critical case given its environmental vulnerabilities, economic challenges, and position within the European sustainability agenda. The empirical results demonstrate a consistent hierarchy (human > produced > natural), significant growth over time, and pronounced regional disparities, with Western and Northern Europe outperforming Eastern and Southern Europe in overall capital stocks. Moreover, human, produced, and natural capital differed significantly (${\eta }_p^2=0.967)$, with the EU-27 dominated by human and produced capital, while Greece lagged substantially (${\eta }_p^2=0.71$). A robust interaction effect indicated structural divergence (${\eta }_p^2=0.811$). The pairwise comparisons confirmed these results with very large effect sizes (Cohen’s d = 2.3–11.2 in the 95% CI). These findings underscore the importance of moving beyond GDP and highlight the policy relevance of inclusive wealth accounting for ensuring resilience and intergenerational equity. Full article

The COVID-19 pandemic triggered unprecedented economic disruptions, raising critical questions about the resilience and adaptability of macroeconomic productivity across countries. This study examines the impact of COVID-19 on macroeconomic efficiency and productivity dynamics in 37 OECD countries using quarterly data from 2018Q1 to 2024Q4. By employing a Slack-Based Measure Data Envelopment Analysis (SBM-DEA) and the Malmquist Productivity Index (MPI), we decompose total factor productivity (TFP) into efficiency change (EC) and technological change (TC) across three periods: pre-pandemic, during-pandemic, and post-pandemic. Our framework incorporates both desirable (GDP) and undesirable outputs (inflation, unemployment, housing price inflation, and interest rate distortions), offering a multidimensional view of macroeconomic efficiency. Results show broad but uneven productivity gains, with technological progress proving more resilient than efficiency during the pandemic. Post-COVID recovery trajectories diverged, reflecting differences in structural adaptability and innovation capacity. Regression analysis reveals that stringent lockdowns in 2020 were associated with lower productivity in 2023–2024, while more adaptive policies in 2021 supported long-term technological gains. These findings highlight the importance of aligning crisis response with forward-looking economic strategies and demonstrate the value of DEA-based methods for evaluating macroeconomic performance beyond GDP. Full article

Happiness is defined as well-being and contentment with life. The growing imperative to evaluate well-being beyond economic growth alone has led to the formulation of holistic indices that better reflect quality of life and sustainable development goals. This has resulted in the emergence of the Happiness Score (HS), which adopts a more holistic and human-centred perspective on development and well-being. The present study takes the Happiness Score as a basis for the identification of some of the main determinants of happiness in an empirical and data-driven perspective. To this end, data from 145 countries was analysed, using statistical methodologies such as Generalised Linear Models (GLM), Principal Component Analysis (PCA), fuzzy set Qualitative Comparison Analysis (fsQCA) and the decision tree machine learning approach. A range of indices were considered to translate the reality of countries in different socio-economic dimensions, the level of development of each country, and the continent to which it belongs. The African continent demonstrates substantial disparities across virtually all variables and is frequently associated with the most unfavourable values for each index. The indicators that exerted the most profound influence on happiness were identified as the freedom to make life choices, literacy rate, and Gross Domestic Product (GDP) per capita. These results inform policy strategies aligned with sustainable development, emphasising that enhancing happiness requires multidimensional action beyond economic indicators—particularly in low- and middle-income countries. Full article

In Latin America, over 50% of the population has relied on loans from family members or friends, reflecting the importance of trust-based networks in response to financial exclusion. This study examines how distrust in the formal financial system influences the use of informal borrowing. Using data from 17 countries for the years 2014, 2017, and 2021, and applying a fixed-effects logistic regression model by country and time, we confirm that rising distrust significantly increases the likelihood of turning to loans from personal networks. This relationship intensifies in times of crisis. Beyond this, we find that macroeconomic variables such as GDP per capita and unemployment also significantly affect informal borrowing behavior. This research contributes to the literature by integrating institutional, economic, and social variables, highlighting the role of interpersonal trust as a form of social capital. It also advances the field of personal finance by revealing an everyday strategy of financial resilience. Finally, this study offers relevant implications for public policy, advocating for a more realistic and context-sensitive approach to financial inclusion, especially in regions where credit constraints in the formal sector have pushed households to seek more accessible and flexible alternatives. Full article

Inclusive growth is increasingly recognized as being critical to sustainable development, particularly in the context of rising income inequality and social polarization around the globe. Effective policy requires robust measurement, prompting the need to move beyond GDP and supplement traditional economic indicators. This study proposes a novel inclusive growth index (IGI) for 73 developing countries. The index is constructed using factor analysis with principal component analysis (PCA) across four pillars: economy, living conditions, equality, and governance. Our results reveal significant heterogeneity among developing countries, largely driven by variations in economic development and governance. Further analysis using OLS regression explores the impact of sectoral transformation, demonstrating a statistically significant positive relationship between shifts from the agricultural to the service sector and the IGI. These findings provide valuable insights for policymakers seeking to create more opportunities and target interventions to achieve more inclusive growth in developing economies. Full article

This study analyses the economic impact of tourism in Iceland, focusing on its contributions to GDP, employment, and foreign currency earnings. This study employs descriptive and comparative secondary data analysis based on available statistics and an extensive literature review to assess the sector’s development, resilience, and sustainability within global and national contexts. The findings confirm that tourism is a key pillar of Iceland’s economy, surpassing traditional export industries in value and generating significant employment opportunities. However, the sector’s volatility exposed during the COVID-19 pandemic and its dependence on international markets reveal structural vulnerabilities that threaten a sustainable future. Beyond economic considerations, this study critically engages with the growing pressures of over-tourism, seasonality, and environmental degradation, particularly in ecologically sensitive areas. Recent scholarship and policy shifts emphasise the need for sustainability indicators, equitable taxation mechanisms, and participatory governance to guide Iceland’s tourism development. This research highlights that balancing economic growth with environmental limits and community well-being is essential for building a more resilient and future-proof tourism model. These insights help inform policymakers, stakeholders, and researchers in aligning tourism strategies with sustainability and diversification goals. Full article