Search Results (286)

The population dynamics of high-altitude mountainous areas are shaped by a complex interplay of socioeconomic and environmental drivers. Despite their significance, such regions have received limited scholarly attention. This research identifies and examines the principal determinants of population changes in the high-altitude mountainous zones of Sichuan Province, China. Utilizing a robust quantitative framework, we introduce the Sustainable Population Migration Index (SPMI) to systematically analyze the migration potential over two decades. The findings indicate healthcare accessibility as the most significant determinant influencing resident and rural population changes, while economic factors notably impact urban populations. The SPMI reveals a pronounced deterioration in migration attractiveness, decreasing by 0.27 units on average from 2010 to 2020. Furthermore, a fixed-effects panel regression confirmed the predictive capability of SPMI regarding population trends, emphasizing its value for demographic forecasting. We also develop a Digital Twin-based Simulation and Decision-support Platform (DTSDP) to visualize policy impacts effectively. Scenario simulations suggest that targeted enhancements in healthcare and infrastructure could significantly alleviate demographic pressures. This research contributes critical insights for sustainable regional development strategies and provides an effective tool for informed policymaking. Full article

Tuberculosis (TB) remains a leading cause of death in Bangladesh, disproportionately affecting low socio-economic status (SES) populations. This review, guided by the WHO Social Determinants of Health framework and Rockefeller-Lancet Planetary Health Report, examined how social, economic, and ecological factors link SES to TB burden. The first literature search identified 28 articles focused on SES-TB relationships in Bangladesh. A second search through snowballing and conceptual mapping yielded 55 more papers of diverse source types and disciplines. Low-SES groups face elevated TB risk due to smoking, biomass fuel use, malnutrition, limited education, stigma, financial barriers, and hazardous housing or workplaces. These factors delay care-seeking, worsen outcomes, and fuel transmission, especially among women. High-SES groups more often face comorbidities like diabetes, which increase TB risk. Broader contextual drivers include urbanisation, weak labour protections, cultural norms, and poor governance. Recommendations include housing and labour reform, gender parity in education, and integrating private providers into TB programmes. These align with the WHO End TB Strategy, UN SDGs and Planetary Health Quadruple Aims, which expand the traditional Triple Aim for health system design by integrating environmental sustainability alongside improved patient outcomes, population health, and cost efficiency. Future research should explore trust in frontline workers, reasons for consulting informal carers, links between makeshift housing and TB, and integrating ecological determinants into existing frameworks. Full article

Dams play a vital role in securing water and electricity supplies for households and industry, and they contribute significantly to flood protection. Regular monitoring of dam deformations holds fundamental socio-economic and ecological importance. Traditionally, this has relied on time-consuming in situ techniques that offer either high spatial or temporal resolution. Persistent Scatterer Interferometry (PSI) addresses these limitations, enabling high-resolution monitoring in both domains. Sensors such as TerraSAR-X (TSX) and Sentinel-1 (S-1) have proven effective for deformation analysis with millimeter accuracy. Combining TSX and S-1 datasets enhances monitoring capabilities by leveraging the high spatial resolution of TSX with the broad coverage of S-1. This improves monitoring by increasing PS point density, reducing revisit intervals, and facilitating the detection of environmental deformation drivers. This study aims to investigate two objectives: first, we evaluate the benefits of a spatially and temporally densified PS time series derived from TSX and S-1 data for detecting radial deformations in individual dam segments. To support this, we developed the TSX2StaMPS toolbox, integrated into the updated snap2stamps workflow for generating single-master interferogram stacks using TSX data. Second, we identify deformation drivers using water level and temperature as exogenous variables. The five-year study period (2017–2022) was conducted on a gravity dam in North Rhine-Westphalia, Germany, which was divided into logically connected segments. The results were compared to in situ data obtained from pendulum measurements. Linear models demonstrated a fair agreement between the combined time series and the pendulum data ($R^2$ = 0.5; MAE = 2.3 mm). Temperature was identified as the primary long-term driver of periodic deformations of the gravity dam. Following the filling of the reservoir, the variance in the PS data increased from 0.9 mm to 3.9 mm in RMSE, suggesting that water level changes are more responsible for short-term variations in the SAR signal. Upon full impoundment, the mean deformation amplitude decreased by approximately 1.7 mm toward the downstream side of the dam, which was attributed to the higher water pressure. The last five meters of water level rise resulted in higher feature importance due to interaction effects with temperature. The study concludes that integrating multiple PS datasets for dam monitoring is beneficial particularly for dams where few PS points can be identified using one sensor or where pendulum systems are not installed. Identifying the drivers of deformation is feasible and can be incorporated into existing monitoring frameworks. Full article

The Mediterranean region is increasingly confronted with intersecting environmental, agricultural, and socio-economic challenges, including biowaste accumulation, soil degradation, and high dependency on imported fossil fuels. Biomethane, a renewable substitute for natural gas, offers a strategic solution that aligns with the region’s need for sustainable energy transition and circular resource management. This review examines the current state of biomethane production in the Mediterranean area, with a focus on anaerobic digestion (AD) technologies, feedstock availability, policy drivers, and integration into the circular bioeconomy (CBE) framework. Emphasis is placed on the valorisation of regionally abundant feedstocks such as olive pomace, citrus peel, grape marc, cactus pear (Opuntia ficus-indica) residues, livestock manure, and the Organic Fraction of Municipal Solid Waste (OFMSW). The multifunctionality of AD—producing renewable energy and nutrient-rich digestate—is highlighted for its dual role in reducing greenhouse gas (GHG) emissions and restoring soil health, especially in areas threatened by desertification such as Sicily (Italy), Spain, Malta, and Greece. The review also explores emerging innovations in biogas upgrading, nutrient recovery, and digital monitoring, along with the role of Renewable Energy Directive III (RED III) and national biomethane strategies in scaling up deployment. Case studies and decentralised implementation models underscore the socio-technical feasibility of biomethane systems across rural and insular territories. Despite significant potential, barriers such as feedstock variability, infrastructural gaps, and policy fragmentation remain. The paper concludes with a roadmap for research and policy to advance biomethane as a pillar of Mediterranean climate resilience, energy autonomy and sustainable agriculture within a circular bioeconomy paradigm. Full article

Food security constitutes a fundamental pillar of future sustainable development. A systematic evaluation of the impact of urban expansion on food security is critical to advancing the United Nations Sustainable Development Goals (SDGs), particularly “Zero Hunger” (SDG 2). Drawing on bibliographic data from the Web of Science Core Collection, this study employs the bibliometrix package in R to conduct a comprehensive bibliometric analysis of the literature on the “urban expansion–food security” nexus spanning from 1982 to 2024. The analysis focuses on knowledge production, collaborative structures, and thematic research trends. The results indicate the following: (1) The publication trajectory in this field exhibits a generally increasing trend with three distinct phases: an incubation period (1982–2000), a development phase (2001–2014), and a phase of rapid growth (2015–2024). Land Use Policy stands out as the most influential journal in the domain, with an average citation rate of 43.5 per article. (2) China and the United States are the leading contributors in terms of publication output, with 3491 and 1359 articles, respectively. However, their international collaboration rates remain relatively modest (0.19 and 0.35) and considerably lower than those observed for the United Kingdom (0.84) and Germany (0.76), suggesting significant potential for enhanced global research cooperation. (3) The major research hotspots cluster around four core areas: urban expansion and land use dynamics, agricultural systems and food security, environmental and climate change, and socio-economic and policy drivers. These focal areas reflect a high degree of interdisciplinary integration, particularly involving land system science, agroecology, and socio-economic studies. Collectively, the field has established a relatively robust academic network and coherent knowledge framework. Nonetheless, it still confronts several limitations, including geographical imbalances, fragmented research scales, and methodological heterogeneity. Future efforts should emphasize cross-regional, interdisciplinary, and multi-scalar integration to strengthen the systematic understanding of urban expansion–food security interactions, thereby informing global strategies for sustainable development. Full article

The relict tree Cercidiphyllum japonicum, a Tertiary paleoendemic with significant ecological and timber value, prefers warm–cool humid climates and acidic soils. Using MaxEnt and ArcGIS, we modeled its distribution under current and future climate scenarios (SSP, Shared Socioeconomic Pathways). High-suitability areas (>0.6 probability) under current conditions are mainly concentrated in the Sichuan Basin and the Yellow–Yangtze transition zones. By 2050, projections show northwestward expansions (14.32–18.76% increase in area) and eastward movement toward Central China under both SSP1-2.6 and SSP5-8.5 scenarios. However, by 2090, habitat loss could exceed 22% under SSP5-8.5. The main environmental drivers of its distribution are minimum coldest-month temperature (bio6, 38.7%), annual precipitation (bio12, 29.1%), and temperature range (bio7, 18.5%). Precipitation seasonality and thermal extremes are expected to become more significant constraints in the future. Conservation strategies should focus on the following: (1) protecting refugia in the Daba–Wushan mountains, (2) facilitating assisted migration to northwestern high-latitude regions, and (3) preserving microclimates. This study offers a framework for evidence-based conservation of paleoendemic species under climate change. Full article

Antimicrobial resistance (AMR) is considered a global healthcare emergency in the 21st century. Although the evolution of microorganisms through Darwinian mechanisms and antibiotic misuse are established drivers, the structural socioeconomic factors of AMR remain insufficiently explored. This review takes on an analytical perspective, drawing upon a wide spectrum of evidence to examine the extent to which socioeconomic factors contribute to the global proliferation of AMR, with an emphasis on low- and middle-income countries (LMICs). The analytical review at hand was carried out through a search for relevant articles and reviews on PubMed, Google Scholar, the Centers for Disease Control and Prevention, and the World Health Organization database using combinations of the keywords “antimicrobial resistance,” “socioeconomic factors,” “low- and middle-income countries,” “surveillance,” “healthcare access,” and “agriculture.” Preference was given to systematic reviews, high-impact primary studies, and policy documents published in peer-reviewed journals or by reputable global health organizations. Our analysis identifies a complex interplay of systemic vulnerabilities that accelerate AMR in resource-limited settings. A lack of regulatory frameworks regarding non-prescription antibiotic use enables the proliferation of multi-drug-resistant microorganisms. Low sewer connectivity facilitates the environmental dissemination of resistance genes. Proper antibiotic selection is hindered by subpar healthcare systems and limited diagnostic capabilities to deliver appropriate treatment. Additionally, gender disparities, forced migration, and climate-driven zoonotic transmission compound the burden. During the COVID-19 pandemic, antimicrobial misuse surged, further amplifying resistance trends. AMR is not solely a biological phenomenon, but a manifestation of global inequity. Mitigation requires a transformation of policy directed toward a “One Health” strategy that incorporates socioeconomic, environmental, and health system reforms. Strengthening surveillance, investing in infrastructure, regulating pharmaceutical practices, and promoting health equity are essential to curb the rising tide of resistance. Full article

Urban green spaces (UGSs), including parks, forests, and community gardens, play a critical role in enhancing public health and well-being by providing essential ecosystem services such as improving air quality, reducing surface temperatures, and mitigating harmful substances. As urbanization accelerates, especially in rapidly growing cities like Jinan, China, the demand for UGSs is intensifying, necessitating careful urban planning to balance development and environmental protection. While previous studies have often focused on city-level green coverage, this study shifts the analytical focus from UGS as a whole to urban functional units (UFUs), allowing for a more detailed examination of how green space is distributed across different land use types. We investigate UGS changes in Jinan over the past two decades and assess the influence of socio-economic factors—such as housing prices, land use types, and building age—on UGS distribution within UFUs. Remote sensing technology was employed to analyze the spatiotemporal dynamics of UGS and its correlation with these variables. Our findings reveal a significant shift in UGS distribution, with parks and leisure areas becoming primary drivers of UGS expansion. This study also highlights the growing influence of economic factors, particularly housing prices, on UGS distribution in more affluent UFUs. Additionally, while UGS in Jinan has generally expanded, challenges remain in balancing green space with urban expansion, especially in commercial and residential UFUs. This paper contributes to a more nuanced understanding of UGS distribution by integrating the UFU framework and identifying socio-economic drivers—including housing prices, construction age, and land use type—that shape green space patterns in Jinan. Our findings demonstrate that the spatial pattern of UGS in Jinan mirrors socio-economic and land use disparities observed in other global cities, highlighting both the universality of these patterns and the need for targeted planning in rapidly urbanizing contexts. Full article

Understanding the trends and drivers of greenhouse gases (GHGs) is vital to making effective climate mitigation strategies and benefiting human health. In this study, we investigate carbon dioxide (CO₂) trends in the top three emitting states in the U.S. (i.e., Texas, California, and Florida) using column-averaged CO₂ concentrations (XCO₂) from the Greenhouse Gases Observing Satellite (GOSAT) from 2010 to 2022. Annual XCO₂ enhancements are derived by removing regional background values (XCO_{2, enhancement}), and their interannual changes (ΔXCO_{2, enhancement}) are analyzed against key influencing factors, including population, gross domestic product (GDP), nonrenewable and renewable energy consumption, and normalized vegetation difference index (NDVI). Overall, interannual changes in socioeconomic factors, particularly GDP and energy consumption, are more strongly correlated with ΔXCO_{2, enhancement} in Florida. In contrast, NDVI and state-specific environmental policies appear to play a more influential role in shaping XCO₂ trends in California and Texas. These differences underscore the importance of regionally tailored approaches to emissions monitoring and mitigation. Although renewable energy use is increasing, CO₂ trends remain primarily influenced by nonrenewable sources, limiting progress toward atmospheric CO₂ reduction. Full article

Soil erosion is a significant environmental challenge in Southwest China, influencing regional ecological security and sustainability. This study investigates the spatiotemporal evolution, driving mechanisms, and future projections of soil erosion in Southwest China, with a focus on the period from 2000 to 2023. The RUSLE model was used to analyze the spatiotemporal variation of soil erosion intensity over the 23-year period in Southwest China. The XGBoost and SHAP models were then employed to identify and interpret the driving factors behind soil erosion. These models revealed that precipitation, temperature, vegetation cover, and land use change were the primary drivers of soil erosion in the region. Finally, future soil erosion risks were projected for 2030, 2040, and 2050 under three climate scenarios (SSP119, SSP245, and SSP585) based on the CMIP6 climate model. The results suggest that (1) the analysis of soil erosion in Southwest China from 2000 to 2023 reveals a significant decline in soil erosion intensity, with a 58.16% reduction in average erosion intensity, from 4.23 t·ha⁻¹·yr⁻¹ in 2000 to 1.77 t·ha⁻¹·yr⁻¹ in 2020. The spatial distribution of erosion in 2023 showed that 90.9% of the region experienced slight erosion, with only 4.56% of the area facing moderate to severe erosion. (2) Natural factors, particularly elevation and precipitation, are the primary drivers of soil erosion. Regions with higher elevations and greater precipitation are more susceptible to soil erosion, particularly on steep slopes with shallow soil layers. Human activities, including GDP growth, land use patterns, and population density, also significantly influence soil erosion dynamics, with higher GDP levels and increased urbanization correlating with elevated erosion risks. The interaction between natural and socioeconomic factors demonstrates a complex relationship in soil erosion processes. (3) By 2050, soil erosion intensity in southwestern China is projected to increase overall, with the most significant increase occurring under the SSP585 scenario. The spatial distribution of soil erosion will largely maintain current patterns, with high-erosion areas concentrated in the northwest and low-erosion areas in the southeast. Areas experiencing mild erosion are expected to decrease, while moderately eroded regions will expand. Projection results suggest that increased precipitation and extreme weather events will lead to the most severe soil erosion in high-altitude regions, particularly in western Sichuan. Our historical assessments and future forecasts suggest vegetation conservation, rainfall monitoring, and restoration of western Sichuan in southwest China are critical for future erosion control and regional ecological security in southwest China. Full article

Understanding the spatiotemporal patterns of cropland carbon and carbon water use efficiency (CWUE) and its driving factors is essential for sustainable agricultural development. Based on a multi-source remote sensing dataset, this study applies a trend analysis (Sen + Mann–Kendall), a dual-type randomized extraction algorithm, and an optimized XGBoost model to examine the spatiotemporal variations in cropland CWUE, including the water use efficiency of net primary production (WUE_NPP), water use efficiency of gross primary production (WUE_GPP), and carbon use efficiency (CUE) in Henan Province from 2001 to 2019. This study further quantifies the impact of irrigation on the cropland CWUE and explores the synergistic effects of its driving factors in irrigated areas. Results reveal significant regional differences in cropland CWUE across Henan Province. Higher multi-year average values of CUE and WUE_NPP were observed in the western region, while the WUE_GPP was more prominent in the south-central region. Over 76% of cropland areas showed a general downward trend in three indicators, with significant interannual declines. Non-irrigated cropland exhibited higher CWUE values than irrigated ones. The average values over multiple years of the WUE_GPP, WUE_NPP, and CUE of irrigated cropland were 2.51 ${\mathrm{g} \mathrm{C} \mathrm{m}}^{-2}{ \mathrm{mm}}^{-1}$, 1.08 ${\mathrm{g} \mathrm{C} \mathrm{m}}^{-2}{ \mathrm{mm}}^{-1}$, and 0.43, respectively. Sunlight was the dominant factor influencing the WUE_GPP in irrigated areas, while precipitation primarily regulated the WUE_NPP and CUE. The influence of the gross domestic product (GDP) was found to be minimal. Notably, both the leaf area index (LAI) and precipitation exhibited a shift from a positive to negative influence on CUE once their values exceeded optimal thresholds, indicating that resource overabundance can lead to physiological limitations. This study offers valuable insights into how irrigated cropland responds to the combined effects of multiple environmental and socio-economic drivers. Full article

Understanding the spatiotemporal dynamics of resource–environment carrying capacity (RECC) is essential for balancing ecological protection and socioeconomic development in river basins. This study applied various methodologies, including Panel Vector Autoregression (PVAR), Geographically Temporally Weighted Regression (GTWR), and Random Forest, to analyze in the Yellow River Basin from 2011 to 2021. PVAR quantifies dynamic interactions among RECC subsystems (population, resources, environment, and economy), while Random Forest identifies nonlinear drivers, and GTWR captures spatiotemporal heterogeneity. Results show RECC performance has continually improved, while subsystem and regional differences have been observed. Downstream regions exhibit higher RECC due to advanced infrastructure, whereas upstream areas face ecological constraints. PVAR results reveal bidirectional relationship among population, resource and economy subsystems, with unidirectional environmental pressure from economic activities. In terms of influencing factors analysis, which are classified into three sections, including geography, socioeconomic, and technological innovation. The random forest model identified that the economic development level has higher importance. The GTWR results expanded the spatiotemporal heterogeneity analysis: socioeconomic factors show significant regional variation. These findings provide a transferable paradigm for complex human–environment system analysis, offering policy-responsive zoning strategies that balance SDG implementation with basin-specific ecological constraints. Full article

Sustainable building rating tools (SBRTs) are essential for assessing the environmental impact of buildings, continuously evolving to meet the needs of users. In Nigeria, the effectiveness of these tools depends on their ability to meet the country’s sustainable building standards and environmental goals. While adopting sustainable building rating tools is crucial for realizing the benefits of sustainable construction, little is known about their actual utilization in the Nigerian construction industry. This research aims to (1) assess the level of awareness and utilization of sustainable building rating tools among diverse stakeholders—including architects, engineers, sustainability consultants, developers, contractors, and suppliers—within Nigeria’s Architecture, Engineering, and Construction (AEC) sector, and (2) explore drivers and barriers to their use. The study adopts an explanatory sequential mixed-methods design, starting with a survey of 98 Nigerian building professionals, followed by qualitative analysis. Results show that while 72.4% were aware of SBRTs, only 39.8% had used them, highlighting a gap between awareness and application. Utilization was higher among professionals with greater experience, income, and education. Barriers included high certification costs, tool complexity, and socio-economic factors, while key drivers were government regulations and environmental benefits. The study calls for targeted education, tool simplification, and financial incentives to boost adoption and promote sustainable construction in Nigeria. Full article

The development of agriculture with special characteristics has become a global trend, especially in highland areas with unique local advantages. Plateau-characteristic agriculture plays an important role in ensuring food security, maintaining ecological balance, and promoting sustainable development in plateau areas. However, because many plateau areas are ecologically fragile and have limited environmental recovery capacity, failure to manage them properly can lead to irreversible environmental degradation and affect socioeconomic stability. Therefore, ensuring plateau-characteristic agroecological security (PCAES) is particularly important and warrants in-depth investigation. However, existing research has yet to systematically identify the key factors affecting PCAES. To fill this gap, this study analyzes 41 factors affecting PCAES at the macro, meso, and micro levels. Then, a DTP (driver–pressure–state–impact–response–management (DPSIRM), technology–environment–resources–economy (TERE), and production–operation–service (POS), collectively referred to as DTP) hierarchy is established to analyze the factors from different perspectives. On this basis, we use a hierarchical decision-making trial and evaluation laboratory (DEMATEL) method to identify nine key factors that influence PCAES, including biodiversity indices, intensity of investment in pollution control, a comprehensive mechanization rate of major crops, and intensity of agricultural R&D investment, among others. Finally, based on the interrelationships among these key factors, we put forward recommendations for PCAES management, taking into account domestic and international experience and the actual situation of the plateau region. Clarifying the factors affecting PCAES will help local governments undertake targeted risk management and scientific decision-making and promote the sustainable development of local economies. Full article

Exploring the spatiotemporal evolution of urban and rural settlements in African countries could provide critical insights into the patterns of urbanization, regional disparities, and sustainable development in the context of rapid socio-economic and demographic changes. Using global human settlement data alongside multi-source socio-economic and environmental datasets, this study investigates the spatiotemporal dynamics of human settlements in Tanzania from 1975 to 2020. A combination of methods, including hotspot analysis, standard deviation ellipse analysis, and geographic detectors, is employed to examine the characteristics of settlement evolution and the underlying factors contributing to regional differentiation. The findings reveal that over the past 45 years, the expansion of urban centers and urban clusters in Tanzania has significantly accelerated, while rural areas have experienced a corresponding decline, reflecting a shift from low-density to high-density settlements and a transformation from rural to urban landscapes. Dar es Salaam, Mwanza, and Arusha have consistently been hotspots for urban center growth, while Kagera has emerged as a primary hotspot for urban clusters. The distribution of rural hotspots and coldspots generally mirrors that of urban clusters. The spatial distribution of urban centers, urban clusters, and rural areas follows a northwest–southeast orientation, with the spatial distribution of urban centers gradually stabilizing. However, the development gap between urban clusters in the northwest and rural areas in the southeast is widening and narrowing, respectively. Socio-economic factors exert a stronger influence on the development of settlements than natural environmental factors. Population density, GDP density, and road network density are significant drivers of settlement patterns, with their influence intensifying over time. Full article