Search Results (15,421)

Growing concerns regarding resource efficiency, economic uncertainty, and energy-market volatility have renewed interest in the relationship between material-use patterns and macroeconomic stability. Recent global disruptions affecting production systems and economic activity have intensified policy attention toward sustainable resource management and resilience-oriented growth strategies. Using an unbalanced panel of 30 OECD economies over the period 1995–2024, this study examines the relationship between resource productivity and economic resilience while accounting for material-use intensity and structural conditions. The empirical framework relies on second-generation panel econometric techniques that account for cross-sectional dependence and heterogeneous country dynamics. The findings indicate that resource productivity is positively associated with economic resilience, with a 1% increase in resource productivity corresponding to an approximately 0.18% increase in resilience. By contrast, domestic material consumption and material footprint display negative associations with resilience, suggesting that resource-intensive production and consumption patterns may be linked to lower adaptive capacity and macroeconomic stability. The short-run estimates additionally indicate the persistence of adjustment dynamics following economic disturbances. These findings highlight the relevance of resource-use efficiency for macroeconomic resilience and sustainable resource-management strategies in OECD economies. Full article

The operationalization of the One Health (OH) approach remains a major challenge due to persistent fragmentation across human, animal, and environmental data systems. This gap is exacerbated by climate change, which acts as a risk multiplier for pathogen transmission and agri-food system vulnerability. Drawing on more than a decade of research, including the re-emergence of brucellosis in Italy and the 2024 Salmonella Umbilo outbreak, this perspective discusses key weaknesses in current data management, particularly the lack of real-time, interoperable data sharing. To address these challenges, we propose an AI-enabled One Health Information System (OH-IS), grounded in FAIR data principles and privacy-preserving architectures. The proposed conceptual framework integrates multi-matrix data streams, combining Earth observation data, genomic surveillance through whole-genome sequencing (WGS), and livestock mobility within a geospatially integrated architecture to support timely decision-making in vulnerable settings. By analyzing the constraints of siloed databases, we discuss how automated semantic harmonization could conceptually support improved risk assessment and outbreak reconstruction in recent zoonotic events. This approach may facilitate a transition from descriptive to anticipatory surveillance, providing a scalable model to move One Health from a conceptual paradigm toward a more integrated and data-driven surveillance framework aligned with EU digital health policies and global health security priorities. Full article

Advancing urban sustainability transitions through effective environmental policies requires understanding how residents perceive and respond to policies. While perceived policy effectiveness (PPE) has been studied in waste management and recycling programs, its role in shaping demand for bio-based materials remains underexplored. This study investigates whether and how PPE is associated with bamboo product consumption among 1121 urban residents in Zhejiang Province, China. Drawing on an extended Theory of Planned Behavior (TPB) framework, we use ordinary least squares estimators to examine the direct and interactive associations between PPE and actual bamboo consumption behavior. Results show that PPE is significantly and positively associated with bamboo product consumption. Interaction analysis reveals heterogeneous effects: PPE shows a weak positive interaction with environmental knowledge, but a negative interaction with environmental values. This suggests that policy signals may complement cognitive preparedness while partly compensating for low value-based motivation. A supplementary analysis indicates that this conditioning extends to economic resources, with the association concentrated among lower-income, more price-sensitive consumers. This study extends PPE research from post-consumption management to the purchasing stage of sustainable products. It highlights the role of policy perceptions in shaping demand-side adoption of lower-impact materials, with implications for urban sustainability transitions and city-level policies promoting bio-based alternatives. Full article

Can China feed itself by 2100? This study begins with a critical reexamination of the bayesTFR recovery assumption embedded in UN WPP 2024 and reconstructs population scenarios using an “empirical-base ± empirical-offset” methodology anchored at China’s 2023 official TFR of 1.01. For food security analysis, we narrow the population to three scenarios (low, medium, and policy target), and we set three scenarios each for the demand side and the supply side, producing an integrated 27-scenario analysis. The demand side comprises three trajectories: East Asian saturation type (650 kg/person/year), EU type (780 kg/person/year), and EU + $\alpha$ type (850 kg/person/year). The supply side comprises three trajectories: optimistic (cropland area maintains the red line, with yield reaching the technological ceiling), medium (climate change reduces yield by $-10\%$, and cropland area breaches the red line by $-5\%$), and pessimistic (climate change reduces yield by $-20\%$, and cropland area breaches the red line by $-10\%$). Based on NBS empirical data, projection results show that all 27 scenarios achieve surplus by 2100 (even the worst case retains 0.265 Gt surplus), confirming the robustness of long-term food security. However, during the medium term (2030–2050), the worst case scenario retains 26% import dependency. Even under the U.S.-type full emulation scenario (1100 kg/person/year) examined as a supplementary stress test, all nine sub-scenarios maintain surplus. The challenge for China’s food security lies not in long-term absolute shortage but in medium-term import dependency management and policy transition to the surplus era. By integrating demographic projection, agricultural-economic demand modeling, and a layered food-system accounting framework, this study offers a transferable cross-disciplinary methodology for long-term food security assessment under demographic transition, relevant beyond China to other aging, post-peak societies. Full article

Open-access satellite data from major Earth observation (EO) missions, including Landsat, Sentinel, and MODIS, have transformed environmental monitoring globally, yet in most least developed countries (LDCs) this data abundance has not translated into operational decisions or policy impact. This review argues that the dominant narrative in the remote sensing community, that open data leads to democratized impact, is fundamentally incomplete. Using Nepal as an illustrative case study, we demonstrate that legal openness alone is insufficient without parallel advances in technical usability and institutional accessibility, the two layers of EO accessibility that the community has largely overlooked. Through a cross-sectoral synthesis spanning forests, agriculture, disaster management, and land cover monitoring, we identify a persistent “last-mile problem”: the systematic gap between data availability and operational governance integration. Systemic barriers including limited internet infrastructure, skills gaps compounded by brain drain, fragmented institutional mandates, and the absence of a national EO coordination mechanism collectively prevent technically sound EO outputs from informing routine planning and policy decisions. Nepal’s small geographic extent, growing digital literacy, and ongoing governance reforms create strategic opportunities for transition, but realizing these requires a functioning geospatial ecosystem integrating data systems, technical infrastructure, human capital, and institutional frameworks. We propose the “Pixels to Policy” framework to operationalize this ecosystem and identify three priority research directions for the global remote sensing community: lightweight data formats for low-bandwidth settings, capacity-aware tool design, and implementation science for EO uptake. These directions reframe the community’s responsibility from delivering open data to ensuring it can be used. Full article

The paper analyses the key challenges and threats to contemporary food security, highlighting the interconnections between large-scale agricultural production and environmental degradation. Selected issues are only a part of this complex phenomenon. The main aim is to initiate a discussion and identify the risks and challenges currently facing agriculture in the context of ensuring food security, and to highlight the potential consequences of treating current agricultural land management practices as a chance for food security. The paper discusses, among other things, the relationship between high-production efficiency and system resilience, and the evolution of the policy framework within the Common Agricultural Policy, which reflects the challenges facing the agricultural sector. A key theme concerns the currently dominant model of agriculture. Particular attention is paid to its negative effects, such as high water consumption, the widespread use of monocultures, the loss of biodiversity, and the excessive use of chemicals and antibiotics. The analysis is further complemented by a discussion of challenges related to safeguarding food security. Overall, the paper underlines the necessity of transforming ways of thinking about food security in the long-term perspective (now and for the future generation) in order to protect natural resources and public health, as well as for reorienting agricultural subsidies towards the support of environmentally sustainable practices. Such a perspective on complex phenomena like food security is essential for maintaining it in the context of escalating crises, including climate change and other global and local challenges. Full article

The research scope comprises the analysis of disjunctions between photographic representations, architectural landmarks, tourist icons, and urbanized surroundings. Given the problem posed by imagery distortions in human cognition, the guiding hypothesis is that the perception of scenes of constructed touristic attractions is distorted with respect to their associated built vicinities. Therefore, the general objective is to systematize guidelines for integrating public policies on visual communication and urban management. Using multi-method, applied, qualitative–quantitative, and exploratory approaches, an investigation is conducted in four main parts: a literature review highlighting knowledge gaps on the topic; procedural methods involving the selection of study areas (cities) and objects (architectures) from those most visited worldwide in the pre-pandemic period followed by submitting their representative photographs for interpretation by experts and the public; analysis involving interpreting respondents’ feedback in association with specific criteria; and an integrated discussion leading to the formulation of directives. As a synthesis of the answers to the research question, the results diagnose a misrepresentation of the immediate and nearby surroundings of architectural sites due to the exclusive observation of images published on official tourism websites, confirming the proposed hypothesis and concluding that the methodological essay is feasible, with case-specific adaptations, as a reference for adequately conveying touristic landscapes in contemporary cities. Full article

Enhancing urban carbon productivity (UCP) is crucial for achieving the dual carbon goals in China. This study investigates the spatiotemporal patterns and underlying drivers of UCP in the Yangtze River Economic Belt (YREB) from 2010 and 2020. Utilizing a comprehensive dataset of 110 cities, we employ kernel density estimation, spatial autocorrelation analysis, and the Spatial Durbin Model (SDM). The results reveal a significant overall improvement in UCP alongside intensified internal disparities and a fundamental spatial restructuring—from a monocentric eastern-led pattern to a multipolar network driven by the Yangtze River Delta, middle Yangtze, and Chengdu-Chongqing agglomerations. The SDM decomposition reveals a shift in core drivers towards green technological innovation and advanced industrial structure, while energy consumption remains the primary constraint. Crucially, complex spatial spillover effects are identified: factors like advanced industrial structure and digital governance are associated with positive synergistic spillovers, whereas government intervention (government public budget expenditure) and urban sprawl exhibit negative competitive spillovers, collectively corresponding to the polarized regional pattern. Furthermore, urban form shows strong spatial externalities: urban compactness is linked to a “local-neighborhood” double dividend, while urban sprawl is associated with a “local-neighborhood” double curse. The influence of digital factors appears to evolve from early widespread spillovers to later localized deepening. The findings suggest the necessity of implementing spatially differentiated policies, strengthening regional collaborative governance to manage spatial externalities, and promoting compact regional spatial planning to foster synergistic and equitable low-carbon transitions across the YREB. Full article

This qualitative study explores perceptions of gender equity and leadership in three higher education institutions in Eswatini. The research involved nine senior management members—deans, registrars, and bursars—and eighteen lecturers (nine women and nine men). Employing narrative inquiry, data were gathered through semi-structured interviews and focus groups, capturing rich individual stories and social dynamics. The study explores how gender influences access to leadership roles, the barriers faced, and potential strategies for fostering inclusive environments. Guided by social role theory, the analysis was deductive, examining how cultural norms and stereotypes shape perceptions of leadership and reinforce gender disparities. Women occupy only 22% of senior management roles, while among lecturers, women constitute 50% of the workforce but only 30% of leadership positions, illustrating persistent under-representation. Findings reveal that despite existing policies, cultural norms rooted in hegemonic masculinity continue to impede gender equity, with organisational biases and societal stereotypes maintaining male dominance in leadership. Participants emphasised that policies must be actively enforced, and cultural change initiatives are essential to challenge stereotypes and reshape societal narratives about gender roles. The study underscores the importance of institutional support, mentorship programmes, and visibility initiatives to empower women and promote gender-inclusive leadership. Engaging men as allies is also critical in transforming organisational culture. These findings contribute to advancing understanding of gender dynamics in Eswatini’s higher education sector and highlight the need for comprehensive, context-specific interventions. Addressing these challenges requires coordinated efforts involving policy enforcement, cultural transformation, capacity building, and ongoing evaluation to ensure sustainable progress toward gender equality in academic leadership. Full article

Heavy-duty transit vehicles (N1–N3) (heavy vehicles) can generate disproportionate environmental and economic impacts in urban transport corridors despite representing a relatively small share of total traffic volume. This study develops an integrated probabilistic framework for assessing the relationships between traffic-flow variability, CO₂e emissions, particulate-matter-derived climate impacts, and external pollution costs associated with transit transport. The methodology combines traffic-flow modeling, emission estimation, PM-to-CO₂e transformation, probabilistic analysis, Monte Carlo simulation, sensitivity analysis, and scenario-based intervention assessment. Separate analyses were conducted for M1 passenger vehicles and heavy vehicles to evaluate differences in emission behavior, uncertainty, and economic impacts. The results indicate substantial structural differences between light-duty and heavy-vehicle regimes. Passenger-car traffic exhibited relatively stable emission distributions, whereas heavy vehicles demonstrated significantly greater variability, uncertainty, and emission intensity. Sensitivity analysis identified heavy-vehicle flow as the dominant factor influencing overall system emissions and pollution costs. Scenario analysis indicated that restrictions targeting heavy-vehicle traffic have the potential to generate considerably larger environmental benefits than generalized traffic-reduction measures. Probabilistic assessment further revealed that heavy vehicles contribute disproportionately to high-emission risk regimes and uncertainty propagation within the system. The proposed framework provides an integrated approach for evaluating climate impacts, uncertainty and economic externalities of transit transport. The results highlight the importance of heavy-vehicle management in reducing emissions and pollution costs while supporting risk-informed transport policy development. Full article

With over 140 species of primary freshwater fish, including 73 that are endemic, Greece is recognized as a biodiversity hotspot in Europe. However, like freshwater systems worldwide, these ecosystems face serious threats, particularly from the introduction of non-native species. This ongoing increase in invasive species has heightened scientific and policy-maker awareness, as such introductions can lead to population declines and even extinctions of native fish. In response to this growing concern, various risk assessment tools have been developed to evaluate the potential hazards posed by non-native species, both those already established and those likely to be introduced. These tools are critical for informing policy decisions and managing biological invasions effectively. In the current study, a new tool, the Hellenic Risk Assessment (HeRA), is proposed. Unlike its predecessors, HeRA places greater emphasis on assessing the biological traits of introduced species and incorporates region-specific considerations tailored to the Mediterranean basin. Its scoring system evaluates both the likelihood of a species establishing itself and its potential environmental impact, making it a valuable resource for stakeholders in prioritizing management actions and making informed decisions regarding the import of live fish species. Full article

Fifth-generation (5G), Beyond 5G (B5G), and sixth-generation (6G) wireless networks, along with the Internet of Things (IoT), are core communication infrastructure in smart cities. Their increased deployments create high-dimensional optimization and resource management challenges. Consequently, researchers have increasingly explored the use of Artificial Intelligence (AI) models for optimizing networks. The Proximal Policy Optimization (PPO) is one such algorithm that optimizes networks. This Systematic Literature Review (SLR) follows the PRISMA 2020 protocol to review 76 studies published between 2023 and 2026 to synthesize recent PPO-based approaches to optimize communication systems. This study examines key PPO variants in major communication domains. It outlines the primary obstacles to real-world deployment and provides a cross-domain classification. According to this study, PPO provides continuous action spaces with good training stability for AI models. Its stable policy-learning capabilities make it suitable for next-generation communication systems. However, sim-to-real transfer, reward design, and multi-agent scalability are a few key challenges encountered. Future directions emphasize robust, deployable PPO frameworks for 6G, IoT, and internet architecture. Full article

This study examines the transformation of environmental governance processes in recreational tourism in Turkey and Lithuania through artificial intelligence (AI)-supported waste management applications. The research focuses on the contributions of AI-based applications to sustainable destination management, environmental sustainability, and data-driven governance processes. A case study design was used within the framework of qualitative research methods. The dataset was obtained through semi-structured interviews with a total of 40 experts from Turkey and Lithuania. The data were analyzed using content analysis with the NVivo 14 program. The research findings reveal significant differences between the two countries in terms of digital infrastructure, institutional coordination, governance structures, and AI integration capacity. In Turkey, AI-supported waste management applications are still in their development phase; processes are largely shaped by managerial initiative, project-based approaches, financial constraints, and lack of institutional coordination. In contrast, Lithuania exhibits a more systematic and institutionalized digital governance structure thanks to EU-supported environmental and digitalization policies. However, data security, system sustainability, and high technology costs in small-scale recreation areas stand out as significant problem areas for Lithuania. This study addresses an underexplored intersection between artificial intelligence applications and environmental governance within recreational tourism contexts, contributing to the emerging literature on digital transformation in sustainable destination management. The findings reveal that AI-supported environmental management systems have significant potential to strengthen sustainable tourism management, increase operational efficiency, and support data-driven sustainable destination strategies. These findings offer practical implications for destination managers and policy makers by highlighting how AI-enabled environmental governance systems can enhance sustainability-oriented decision-making and improve operational efficiency in recreational tourism areas. Full article

This paper examines the structural changes that the Indian equity market has experienced between 2015 and 2025 under the influence of major macroeconomic and geopolitical shocks—including the November 2016 demonetisation, the IL&FS liquidity crisis of 2018, the COVID-19 pandemic of 2020–2021, the Russo–Ukrainian conflict of 2022, and the synchronised global monetary tightening of 2022–2024. The primary objective is to test whether the volatility-modelling architecture proposed by a 2017 benchmark study for the 1992–2016 period continues to hold under the structurally different post-2015 regime, and to identify how persistence, asymmetry, and ARCH-order properties have evolved across the BSE Sensex, NSE CNX Nifty, and twenty-seven sectoral indices. A unified GARCH-family framework comprising GARCH(1,1), GJR-GARCH(1,1), and GARCH(2,1) is estimated on daily log-returns over an eleven-year sample of approximately 2750 observations per index. The empirical evidence confirms that volatility clustering and persistence are pervasive in the post-2015 decade, with the persistence measure (α1 + β1) rising relative to the initial 2017 study for most indices. Asymmetric volatility has intensified—negative shocks generate disproportionately larger volatility responses than positive shocks, particularly in the banking, FMCG, and energy sectors. A higher-order GARCH(2,1) specification is the preferred model for four indices in which lag-2 ARCH effects remain significant or in which integrated-GARCH behaviour rules out the standard GARCH(1,1). The findings have direct implications for portfolio risk management, option pricing, and the design of prudential policy in an increasingly retail-driven and derivative-intensive market ecosystem. Full article

Shaded Arabica coffee production in agroforestry systems, as opposed to full-sun production, is a nature-based solution improving soil water balance, reducing heat exposure of coffee plants, and supporting sustainable forest management as opposed to deforestation. For this coffee production system in Mexico, which is dominated by smallholders as the largest group of coffee producers, we herein analyze current and estimate future yields. For the first time, to our best knowledge, this is done with a process-based coffee agroforestry model CAF2014 that we adapted for geo-spatial applications and named CAF2014-Rhaobi. Modeling of smallholders’ representative management is based on tree thinning, pruning frequency, and nitrogen supply through fertilizer and litter from nitrogen-fixing shade trees. Modeled historical yields generally agree with the reported numbers; however, there are discrepancies explained by modeling assumptions and simplifications. While shade trees help sustain coffee production, the projected drop in yields under present management is about 30% at the end of the century compared to the present as estimated using an ensemble of CMIP6 SSP5-8.5 climate projections. Economic analysis for three typologies of Mexican small coffee producers (conventional low, high-efficiency, and organic) reveals the major role of farmer associations and organic coffee price premiums in making production economically sustainable. This emphasizes the need for innovative marketing approaches and policies supporting farmers opting for certified production. Full article