Search Results (1,674)

Urban air pollution remains a critical public health issue, especially in densely populated cities where pedestrians experience direct exposure to traffic-related and environmental emissions. This study develops and tests a pollution-aware pedestrian routing framework for Thessaloniki, Greece, designed to minimize environmental exposure while maintaining route efficiency. The framework combines high-resolution air-quality data and computational techniques to represent pollution patterns at pedestrian scale. Air-quality is expressed as a continuous European Air Quality Index (EAQI) and is embedded in a network-based routing engine (OSRM) that balances exposure and distance through a weighted optimization function. Using 3000 randomly sampled origin-destination pairs, exposure-aware routes are compared with conventional shortest-distance paths across short, medium, and long walking trips. Results show that exposure-aware routes reduce cumulative AQI exposure by an average of 4% with only 3% distance increase, while maintaining stable scaling across all route classes. Exposure benefits exceeding 5% are observed for approximately 8% of medium-length routes and 24% of long routes, while short routes present minimal or no detours, but lower exposure benefits. These findings confirm that integrating high-resolution environmental data into pedestrian navigation systems is both feasible and operationally effective, providing a practical foundation for future real-time, pollution-aware mobility services in smart cities. Full article

Urban vitality is a crucial indicator of a city’s sustainable development and the quality of life of its residents. Investigating the spatiotemporal patterns and influencing mechanisms of urban vitality is essential for optimizing the built-environment and improving governance. Using the central urban area of Guiyang, China, as a case study, this research integrates multi-source urban sensing data to investigate the spatiotemporal patterns of urban vitality and their driving factors. Geographically weighted regression (GWR) and machine learning combined with SHapley Additive exPlanations (SHAP) are applied to capture spatial heterogeneity, nonlinear relationships, and threshold effects among influencing variables. Results show that urban vitality exhibits a Y-shaped, single-core, multi-center, and clustered spatial configuration, with slightly higher intensity on weekdays and similar diurnal rhythms across weekdays and weekends. The effects of influencing factors display strong spatial non-stationarity, characterized by a concentric gradient radiating outward from the historic Laocheng core. Building density (BD), residential point density (RED), normalized difference vegetation index (NDVI), and road density (RD) emerge as the dominant contributors to urban vitality, while topographic conditions play a relatively minor role. The relationships between key landscape and built-environment variables and urban vitality are highly nonlinear, with distinct threshold effects. By integrating spatial econometric modeling and explainable machine learning, this study advances methodological approaches for urban vitality research and provides practical insights for landscape-oriented urban planning and human-centered spatial design. Full article

The global consensus on sustainable development hinges on the coordinated advancement of economic, social, and environmental dimensions, with high-quality development serving as China’s pivotal pathway for practical implementation. As the primary implementers, cities are confronted with the dual challenge of defining the level of high-quality development and mapping out clear actionable pathways. Therefore, unraveling the driving mechanisms of high-quality urban development is significant. This study constructed a high-quality development evaluation index system, employing a sustainable development index to measure Lianyungang City’s development level from 2008 to 2023. The interrelationships among driving factors were revealed through the coupling coordination degree model, entropy weight method, and Pearson correlation coefficient. The study indicated that innovation stood out as the primary contributor, with contribution rising from 0.09 (2008–2017) to 0.10 (2017–2023). High-tech enterprises and valid invention patents were core drivers of the innovation index’s rise, with weights of 30.35% and 28.92%. Innovation investment promoted the transformation of cities toward technology-intensive development models while effectively supporting Sustainable Development Goals such as industrial upgrading, environmental improvement, and livelihood enhancement. Overall, advancing high-quality urban development required focusing on innovation-driven strategies while catalyzing other areas of development to achieve Sustainable Development Goals. Full article

Background: Population aging has increased attention on the quality of life and successful aging of older adults. Objective: To examine urban–rural differences in subjective quality of life and self-rated successful aging, explore associations with psychosocial factors, and identify predictors of successful aging, including potential moderating effects of place of residence and chronic illness. Methods: A cross-sectional study was conducted among 403 adults aged ≥ 60 years in Eastern Croatia. Measures included a sociodemographic questionnaire, the Self-assessment of Successful Aging Scale (SSAS), and the Personal Wellbeing Index (PWI). Data were analyzed using nonparametric tests (Mann–Whitney U, Spearman’s correlation), linear regression, and moderation analyses. Significance was set at p < 0.05. Ethical approval was obtained (Class: 602-01/24-12/02; IRB: 2158/97-97-10-24-36). Results: Rural participants reported lower PWI scores (p = 0.005) and self-rated successful aging (p < 0.001) than urban participants. Active community involvement was positively associated with quality of life (Rho = 0.46; p < 0.001), whereas regret about missed opportunities and past actions was negatively associated (Rho = −0.20; p < 0.01). Regression analyses explained 48.3% of the variance in SSAS, with higher PWI scores being strongly associated with higher SSAS scores, and rural residence and chronic illness being associated with lower SSAS scores. Moderation analyses indicated that the association between PWI and SSAS was consistent across different environmental contexts and in the presence of illness. Conclusions: Older adults living in rural areas reported lower quality of life and self-rated successful aging compared with those in urban and suburban areas, with subjective wellbeing emerging as a key predictor. Promoting social engagement and addressing psychosocial barriers may enhance successful aging, particularly in rural populations. Findings suggest that social engagement and psychosocial support are associated with higher level of perceived successful aging, indicating potential areas for future community-based or healthcare interventions. Full article

Rapid urbanization and anthropogenic activities have led to a significant deterioration of air quality, adversely affecting human health and ecosystems. The study of transboundary river basins, where air pollution is exacerbated by political and socio-economic factors, is of particular relevance. This paper presents the results of an analysis of the spatiotemporal distribution of pollutants (Aerosol Index (AI), Methane (CH₄), Carbon Monoxide (CO), Formaldehyde (HCHO), Nitrogen Dioxide (NO₂), Ozone (O₃), Sulfur Dioxide (SO₂)) in the ambient air within the Orontes River basin across Lebanon, Syria, and Turkey for the period 2019–2024. The research is based on satellite monitoring data (Copernicus Sentinel-5P), processed using the Google Earth Engine (GEE) cloud-based platform and GIS technologies (ArcGIS 10.8). The dynamics of population density (LandScan) and the impact of military operations in Syria on air quality were additionally analyzed using media content analysis. The results showed that the highest concentrations of pollutants were recorded in Syria, which is associated with the destruction of infrastructure, military operations, and unregulated emissions. The main sources of pollution were: explosions, fires, and destruction during the conflict (aerosols, CO, NO₂, SO₂); methane (CH₄) leaks from damaged oil and gas facilities; the use of low-quality fuels and waste burning. Atmospheric circulation contributed to the eastward transport of pollutants, minimizing their spread into Lebanon. Population density dynamics are related to changes in concentrations of pollutants (e.g., nitrogen dioxide). The results of the study highlight the need for international cooperation to monitor and reduce air pollution in transboundary regions, especially in the context of armed conflicts. The obtained data can be used to develop measures to improve the environmental situation and protect public health. Full article

Rapid urbanization has significantly affected urban ecological environments, necessitating accurate and scientific quality assessments. In this study, we develop an enhanced remote sensing ecological index (WRSEI) for water network cities using Linyi City, China, as a case study. Key innovations include (1) introducing a water–vegetation index to better represent aquatic ecosystems; (2) incorporating nighttime light data to quantify the intensity of human activity; and (3) employing hierarchical PCA to rationally weight ecological endowment and stress indicators. The model’s effectiveness was rigorously validated using independent land use data. The results show that (1) the WRSEI accurately captures Linyi’s “water–city symbiosis” pattern, increasing the assessed ecological quality of water bodies by 15.78% compared to the conventional RSEI; (2) hierarchical PCA provides more ecologically reasonable indicator weights; and (3) from 2000 to 2020, ecological quality exhibited a pattern of “central degradation and peripheral improvement”, driven by urban expansion. This study establishes a validated technical framework for ecological assessment in water-rich cities, offering a scientific basis for sustainable urban management. Full article

Historic waterfront streets are not only an important component of urban public spaces but also highlight the distinctive features and historical contexts of the city. High-quality streetscape visual perception plays a crucial role in advancing the cultural, social, environmental, and economic sustainability of the urban street space. This study was initiated to construct a multi-dimension and multi-scale comprehensive evaluation framework to assess the visual quality of waterfront streets, taking “Water City” Liaocheng as a typical case. Technical methods of semantic segmentation, sDNA (Spatial Design Network Analysis), GIS (Geographic Information System), and statistical analysis were utilized. Following the extraction and classification of street space elements, a multi-dimensional evaluation index system of natural coordination, artificial comfort, and historical culture for the visual assessment was established. Space syntax was performed on waterfront streets by sDNA to quantify macro-level scale spatial structure and meso-level scale pedestrian accessibility. The results of micro-scale visual perception, meso-scale behavioral walkability, and macro-scale spatial structure, were integrated to construct a multi-scale diagnostic framework for eight classifications. This framework provides a scientific basis to put forwards the refined and sustainable optimization strategies for historic waterfront streets. Full article

Air pollution represents one of the foremost environmental and public health challenges of the twenty-first century, with differentiated impacts according to the socio-economic and urban conditions of affected populations. It therefore remains necessary to integrate social and spatial factors into air quality assessment, going beyond purely physicochemical approaches. This study aims to develop a socio-environmental index to assess air quality (SAQI) based on particulate matter (PM) concentrations in two urban areas of Bogota (Colombia). The methodology is structured in three phases: (i) a global review of reported socio-environmental indices over the past decade, (ii) construction of the index via integration of environmental and socio-economic variables collected in the locality of Kennedy, and (iii) comparative validation of the index in the locality of Barrios Unidos to assess robustness and transferability. The structure of the proposed SAQI assigns 45% weight to the socio-economic dimension and 55% to environmental exposure (PM_2.5 and PM₁₀ concentrations). During the development phase in Kennedy, annual PM_2.5 concentrations were systematically found to exceed World Health Organization guidelines by factors ranging between 4.0 and 5.7 (24.5 ± 2.89 µg/m³). The comparative application in Barrios Unidos (SAQI = 12, “good”) and Kennedy (SAQI = 21.8, “acceptable”) revealed an 81.5% socio-environmental gap driven by PM concentrations up to 49.8% higher and greater social vulnerability in Kennedy. The methodological divergence compared to the local technical index—IBOCA (45.2 in Kennedy)—underscores the added value of the SAQI developed to capture effective socio-environmental risk. The SAQI developed in this work is a potential decision-making tool that guides public policies toward fairer and more equitable air quality management in urban areas of developing countries. Full article

E-scooters have become a widely adopted form of urban mobility, increasing the need to understand how vibration exposure affects comfort and safety. While most studies have examined the effects of speed, pavement roughness, and overall tire stiffness, none have evaluated how differing stiffness curves between the front and rear wheels influence rider comfort. This article uses real stiffness curves for rigid and inflatable tires at various pressures (30 psi, 60 psi, and rigid) to assess how front–rear stiffness asymmetry affects vibration transmission across speeds (10–20–30 km/h) and two roughness levels (low and high). The analysis, following the standard UNE-ISO 2631-1:2008 and supported by a multiple-regression model (adjusted R² = 93.84%, homoscedastic residuals), shows that speed and roughness dominate the comfort response (98.9%), while tire stiffness offers a secondary (1.1%) but useful tuning parameter, inducing comfort index variations exceeding 14% between front–rear pressure combinations under typical urban conditions (~20 km/h, low roughness). In this case, the most favorable configuration corresponds to inflatable tires with slightly higher front pressure (+2.9–4.35 psi), whereas solid tires consistently yield the poorest comfort. These findings underscore the role of front–rear stiffness management in improving ride quality and provide practical guidance for optimal inflation strategies in urban e-scooters. Full article

Smart city initiatives increasingly rely on interoperable and high-quality urban data, yet many cities lack systematic methods for prioritizing which datasets should be developed first. This study proposes an evidence-based framework for smart city data prioritization that integrates data need, data availability, and policy urgency into a unified decision-support model. Using standardized data elements across seven nationally defined smart city domains, the framework was applied to thirty-six certified smart cities in Thailand. Data were collected from municipal authorities and national platforms and structured using ISO-based data element and metadata principles. For each data element, a Need Priority Index, Coverage score, and Policy Readiness indicator were computed to assess governance-relevant data readiness. The results reveal a persistent imbalance between high data demand and low data availability across all domains, with Smart Mobility, Smart Living, Smart Energy, and Smart Economy showing the highest urgency. A Core Common Data Set representing 6.7% of assessed properties was identified, centered on population data, geospatial infrastructure, and plans and performance indicators. The framework provides a scalable approach for guiding investments in interoperable smart city data systems. Full article

Sustainable groundwater management is critical in semi-arid coastal regions, where municipal landfills pose a severe threat to aquifer integrity and long-term water security. However, there is still a lack of seasonally resolved hydrogeochemical monitoring around newly established landfills, particularly in rapidly urbanizing Mediterranean settings. This study assesses the hydrogeochemical impact of the newly operational Tangier Landfill and Recovery Center on local groundwater resources to inform sustainable remediation strategies. A combined approach was applied to samples collected in dry and wet seasons, using Piper and Stiff diagrams to trace facies evolution together with a dual-index assessment based on the Canadian (CCME-WQI) and Weighted Arithmetic (WAWQI) Water Quality Indices. Results show that upgradient waters remain of Good–Excellent quality and are dominated by Ca–HCO₃ facies, whereas downgradient wells display extreme mineralization, with EC up to 15,480 µS/cm and Cl⁻ and SO₄²⁻ exceeding 1834 and 2114 mg/L, respectively. At hotspot sites P4 and P8, As reaches 0.065 mg/L and Cd 0.006 mg/L, far above the WHO drinking-water guidelines. While the CCME-WQI captures the general salinity-driven degradation pattern, the WAWQI pinpoints these acute toxicity zones as Very poor–Unsuitable. The study demonstrates that rainfall intensifies toxicity through a seasonal “Piston Effect” that mobilizes stored contaminants rather than diluting them, underscoring the need for seasonally adaptive monitoring to ensure the environmental sustainability of landfill-adjacent aquifers. Full article

Driven by the globalization tide, urbanization and cross-border economic cooperation have intensified challenges to ecological conservation, with border regions increasingly confronting irreversible habitat degradation risks. As a globally recognized biodiversity hotspot, Xishuangbanna acts as a strategic hub for cross-border ecological security between China and Southeast Asia, having long been confronted with dual pressures from economic development and ecological conservation. By analyzing the spatiotemporal evolution of the Remote Sensing Ecological Index (RSEI) during 2003–2023, this study simulates its multi-scenario dynamics, develops the “RSEI-ESP-PLUS” framework, presents a novel assessment mechanism for ecological security patterns (ESP), and provides a scientific basis for regional sustainable development. Results indicate that integrating RSEI improves the accuracy of ecological source identification. Over the past two decades, regional Ecological Environmental Quality has exhibited an overall improvement trend, yet persistent ecological pressures remain—including vegetation degradation and climate warming. Concurrently, high-quality ecological areas have contracted while moderate-quality ones have expanded. In the 2033 simulation, the ecological conservation scenario delivered the most favorable ecological network assessment outcomes, identifying 16 stable and 15 potential ecological sources. Accordingly, this study establishes an ecological security pattern centered on the core structure of the “One Axis, Two Corridors, and Three Zones”, which provides a spatial planning scheme for regional sustainable development. Full article

Quality control of drinking water is essential for safeguarding public health, particularly in densely populated urban environments. Environmental microbiological monitoring can complement conventional surveillance by providing deeper insights into the dissemination of pathogens and antimicrobial resistance genes within aquatic systems. In this study, we assessed the quality of wastewater and treated water from two urban water supply systems, representing the southern and northern regions of Porto Alegre, Rio Grande do Sul, Brazil, across four climatic seasons between 2024 and 2025. Fifteen water samples were analyzed, including raw water from Guaíba Lake and treated water collected from public distribution points. The Water Quality Index was calculated, microbiological indicators were quantified, and carbapenem resistance genes were detected using molecular assays. Most treated water samples complied with established bacteriological standards; however, the bla_OXA-48-like gene was recurrently detected in both wastewater and treated water. No resistance genes were identified during the summer, whereas the bla_VIM gene was detected exclusively in spring samples. The presence of carbapenem resistance genes in the absence of cultivable coliforms suggests the persistence of extracellular DNA or viable but non-culturable bacteria, highlighting limitations inherent to conventional microbiological monitoring. Integrating classical microbiological methods with molecular assays enables a more comprehensive assessment of water quality and strengthens evidence-based decision-making within a One Health framework. Full article

This follow-up study investigates the long-term environmental sustainability and remediation outcomes of the UPPER (‘Urban Productive Parks for Sustainable Urban Regeneration’-UIA04-252) project in Latina, Italy, focusing on Nature-Based Solutions (NbS) applied to urban green infrastructure. By integrating proximal and satellite-based remote sensing methodologies, the research evaluates persistent improvements in vegetation health, soil moisture dynamics, and overall environmental quality over multiple years. Building upon the initial monitoring framework, this case study incorporates updated data and refined techniques to quantify temporal changes and assess the ecological performance of NbS interventions. In more detail, ground-based data from meteo-climatic, air quality stations and remote satellite data from the Sentinel-2 mission are adopted. Ground-based measurements such as temperature, humidity, radiation, rainfall intensity, PM10 and PM2.5 are carried out to monitor the overall environmental quality. Updated satellite imagery from Sentinel-2 is analyzed using advanced band ratio indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Moisture Index (NDMI). Comparative temporal analysis revealed consistent enhancements in vegetation health, with NDVI values significantly exceeding baseline levels (NDVI 2022–2024: +0.096, p = 0.024), demonstrating successful vegetation establishment with larger gains in green areas (+27.0%) than parking retrofits (+11.4%, p = 0.041). However, concurrent NDWI decline (−0.066, p = 0.063) indicates increased vegetation water stress despite irrigation infrastructure. NDMI improvements (+0.098, p = 0.016) suggest physiological adaptation through stomatal regulation. Principal Component Analysis (PCA) of meteo-climatic variables reveals temperature as the dominant environmental driver (PC2 loadings > 0.8), with municipality-wide NDVI-temperature correlations of r = −0.87. These multi-scale findings validate sustained NbS effectiveness in enhancing vegetation density and ecosystem services, yet simultaneously expose critical water-limitation trade-offs in Mediterranean semi-arid contexts, necessitating adaptive irrigation management and continued monitoring for long-term urban climate resilience. The integrated monitoring approach underscores the critical role of continuous, multi-scale assessment in ensuring long-term success and adaptive management of NbS-based interventions. Full article

High-quality development of agricultural enterprises is essential for China’s rural revitalization, yet the institutional conditions that support it remain poorly understood. Drawing on institutional logics and configuration theory, this study adopts a holistic systems perspective to examine how government, market, and social institutions interact to shape enterprise performance. Using provincial data (2013–2023) matched with firm-level data for 119 listed agricultural enterprises, we estimate total factor productivity as the core outcome and apply dynamic fuzzy-set Qualitative Comparative Analysis (dynamic fsQCA) to identify equifinal institutional pathways. The results reveal that high-quality development is an emergent property of complex institutional systems; instead, high-quality development emerges from several distinct configurations combining policy support, marketization, financial development, Agricultural Infrastructure Index, market stability, and urban–rural integration. Two contrasting configurations are associated with non-high-quality development, characterized by financial scarcity and infrastructure deficits or by fragmented policy support under weak regulation. Dynamic analysis further reveals clear temporal and spatial heterogeneity: some market–finance driven paths lose robustness over time, while policy–urbanization and regulation–infrastructure based configurations become increasingly stable. These findings extend institutional configuration research to the agricultural sector, demonstrate the value of dynamic fsQCA for capturing temporal effects, and offer differentiated policy implications for optimizing institutional environments to foster the high-quality development of agricultural enterprises. Full article