Search Results (152)

The escalating environmental noise pollution along urban rail transit corridors, exacerbated by rapid urbanization, necessitates innovative and efficient noise control measures. A comprehensive investigation was conducted that utilized field measurements of train passing-by noise to establish a statistical energy analysis model for evaluating the acoustic performance of both vertical (VB) and fully enclosed (FB) barrier configurations. The study incorporated Maa’s theory of micro-perforated plate (MPP) parameter optimization and developed a neural network surrogate model focused on insertion loss maximization for barrier geometric design. Key findings revealed significant barrier-induced near-track noise amplification, with peak effects observed at the point located 1 m from the barrier and 2 m above the rail. Frequency-dependent analysis demonstrated a characteristic rise-and-fall reflection pattern, showing maximum amplifications of 1.47 dB for VB and 4.13 dB for FB within the 400–2000 Hz range. The implementation of optimized MPPs was found to effectively eliminate the near-field noise amplification effects, achieving sound pressure level reductions of 4–8 dB at acoustically sensitive locations. Furthermore, the high-precision surrogate model (R² = 0.9094, MSE = 0.8711) facilitated optimal geometric design solutions. The synergistic combination of MPP absorption characteristics and geometric optimization resulted in substantially enhanced barrier performance, offering practical solutions for urban rail noise mitigation strategies. Full article

Under the continuous disturbance of ecosystems driven by urbanization, landscape fragmentation and the disruption of ecological processes and functions are key challenges in optimizing ecological networks (EN). This study aims to examine the spatiotemporal evolution of topological patterns, ecological processes, and ecosystem services (ES) in Wuhan from the “pattern–process–function” perspective. To overcome the lag in research concerning the coupling of ecological processes, functions, and spatial patterns, we explore the long-term dynamic evolution of ecosystem structure, process, and function by integrating multi-source data, including remote sensing, enabling comprehensive spatiotemporal analysis from 2000 to 2020. Addressing limitations in current EN optimization approaches, we integrate morphological spatial pattern analysis (MSPA), use circuit theory to identify EN components, and conduct spatial optimization accurately. We further assess the effectiveness of two scenario types: “pattern–function” and “pattern–process”. The results reveal a distinct “increase-then-decrease” trend in EN structural attributes: from 2000 to 2020, source areas declined from 39 (900 km²) to 37 (725 km²), while corridor numbers fluctuated before stabilizing at 89. Ecological processes and functions exhibited phased fluctuations. Among water-related indicators, water conservation (as a core function), and modified normalized difference water index (MNDWI, as a key process) predominantly drive positive correlations under the “pattern–function” and “pattern–process” scenarios, respectively. The “pattern–function” scenario strengthens core area connectivity (24% and 4% slower degradation under targeted/random attacks, respectively), enhancing resistance to general disturbances, whereas the “pattern–process” scenario increases redundancy in edge transition zones (21% slower degradation under targeted attacks), improving resilience to targeted disruptions. This complementary design results in a gradient EN structure characterized by core stability and peripheral resilience. This study pioneers an EN optimization framework that systematically integrates identification, assessment, optimization, and validation into a closed-loop workflow. Notably, it establishes a quantifiable, multi-objective decision basis for EN optimization, offering transferable guidance for green infrastructure planning and ecological restoration from a pattern–process–function perspective. Full article

The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO₂ and PM_2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO₂, PM_2.5, and PM₁₀, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article

Indoors, the infection risk of diseases transmitted through the airborne route is estimated from indoor carbon dioxide (CO₂) levels. However, the approaches to assess this risk do not account for the airborne concentration of pathogens, among other limitations. In this study, we analyzed the relationship between airborne SARS-CoV-2 levels and environmental parameters. Bioaerosols were sampled (n = 40) in hospital corridors of two wards differing in the COVID-19 severity of the admitted patients. SARS-CoV-2 levels were quantified using droplet digital PCR. SARS-CoV-2 was detected in 60% of the total air samples. The ward where the mildly ill patients were admitted had a higher occupancy, transit of people in the corridor, and CO₂ levels, but there were no significant differences in SARS-CoV-2 detection between wards. The mean CO₂ concentration in the positive samples was 569 ± 35.6 ppm. Considering all samples, the CO₂ levels in the corridor were positively correlated with patient door openings but inversely correlated with SARS-CoV-2 levels. In conclusion, airborne SARS-CoV-2 can be detected indoors with optimal ventilation, and its levels do not scale with CO₂ concentration in hospital corridors. Therefore, CO₂ assessment should not be interpreted as a surrogate of airborne viral presence in all indoor spaces. Full article

Rapid urbanization and climate change pose significant challenges to air quality in arid metropolitan areas, with critical implications for public health and sustainable development. This study projects the evolution of air pollution in Riyadh, Saudi Arabia, through 2070 using an integrated modeling approach that combines CMIP6 climate projections with localized air quality data. We analyzed daily concentrations of major pollutants (SO₂, NO₂) across 15 strategically selected monitoring stations representing diverse urban environments, including traffic corridors, residential areas, healthcare facilities, and semi-natural zones. Climate data from two Earth System Models (CNRM-ESM2-1 and MPI-ESM1.2) were bias-corrected and integrated with historical pollution measurements (2000–2015) using hierarchical Bayesian statistical modeling under SSP2-4.5 and SSP5-8.5 emission scenarios. Our results revealed substantial deterioration in air quality, with projected increases of 80–130% for SO₂ and 45–55% for NO₂ concentrations by 2070 under high-emission scenarios. Spatial analysis demonstrated pronounced pollution gradients, with traffic corridors (Eastern Ring Road, Northern Ring Road, Southern Ring Road) and densely urbanized areas (King Fahad Road, Makkah Road) experiencing the most severe increases, exceeding WHO guidelines by factors of 2–3. Even semi-natural areas showed significant increases in pollution due to regional transport effects. The hierarchical Bayesian framework effectively quantified uncertainties while revealing consistent degradation trends across both climate models, with the MPI-ESM1.2 model showing a greater sensitivity to anthropogenic forcing. Future concentrations are projected to reach up to 70 μg m⁻³ for SO₂ and exceed 100 μg m⁻³ for NO₂ in heavily trafficked areas by 2070, representing 2–3 times the Traffic corridors showed concentration increases of 21–24% compared to historical baselines, with some stations (R5, R13, and R14) recording projected levels above 4.0 ppb for SO₂ under the SSP5-8.5 scenario. These findings highlight the urgent need for comprehensive emission reduction strategies, accelerated renewable energy transition, and reformed urban planning approaches in rapidly developing arid cities. Full article

This study focuses on the Dongting Lake region in China and evaluates ecological vulnerability using the Sensitivity–Resilience–Pressure (SRP) framework, integrated with Spatial Principal Component Analysis (SPCA) to calculate the Ecological Vulnerability Index (EVI). The EVI values were classified into five levels using the Natural Breaks (Jenks) method, and spatial autocorrelation analysis was applied to reveal spatial differentiation patterns. The Geodetector model was used to analyze the driving mechanisms of natural and socioeconomic factors on EVI, identifying key influencing variables. Furthermore, the LightGBM algorithm was used for feature optimization, followed by the construction of six machine learning models—Multilayer Perceptron (MLP), Extremely Randomized Trees (ET), Decision Tree (DT), Random Forest (RF), LightGBM, and K-Nearest Neighbors (KNN)—to conduct multi-class classification of ecological vulnerability. Model performance was assessed using ROC–AUC, accuracy, recall, confusion matrix, and Kappa coefficient, and the best-performing model was interpreted using SHAP (SHapley Additive exPlanations). The results indicate that: ① ecological vulnerability increased progressively from the core wetlands and riparian corridors to the transitional zones in the surrounding hills and mountains; ② a significant spatial clustering of ecological vulnerability was observed, with a Moran’s I index of 0.78; ③ Geodetector analysis identified the interaction between NPP (q = 0.329) and precipitation (PRE, q = 0.268) as the dominant factor (q = 0.50) influencing spatial variation of EVI; ④ the Random Forest model achieved the best classification performance (AUC = 0.954, F1 score = 0.78), and SHAP analysis showed that NPP and PRE made the most significant contributions to model predictions. This study proposes a multi-method integrated decision support framework for assessing ecological vulnerability in lake wetland ecosystems. Full article

The Yangtze River Economic Belt (YEB), serving as a pivotal transportation corridor connecting eastern and western China and a national strategic development hub, plays a central role in driving high-quality economic development (HQAED) across the country. Based on the new development paradigm with emphasis on green transformation and transportation integration, this study proposes a comprehensive evaluation framework for an HQAED index (HQAED) across five core dimensions. Employing the entropy-weighted CRITIC method to quantify provincial HQAED values, combined with Dagum–Gini coefficient analysis to examine regional inequality patterns and determinants, and complemented by kernel density estimation (KDE) for temporal dynamics analysis, this research reveals four key findings: (1) There are significant disparities in HQEDI levels across the YEB, with a clear east–west gradient: the lower reaches > middle reaches > upper reaches. (2) While the dimensions of green development and shared development have shown steady growth despite initial disadvantages, the openness dimension faces structural challenges that require particular attention. (3) The overall Gini coefficient fluctuates between 0.068 and 0.094, indicating moderate regional disparities with relatively limited inequality. (4) The rightward shift in the HQEDI kernel density curves confirms overall progress, but also highlights widening disparities in the upstream regions and growth stagnation in the midstream areas. Practically, the entropy–CRITIC fusion methodology offers a transferable framework for emerging economies measuring sustainability-transition progress, while the quantified “green transportation empowerment” effects provide actionable levers for policymakers to optimize ecological compensation mechanisms and cross-regional infrastructure investments. Full article

Understanding the relationships between diversity and functional traits in plant communities is essential for elucidating ecosystem functions, forecasting community succession, and informing ecological restoration efforts in arid regions. Although the current research on plant functional traits and diversity has improved our ability to predict ecological functions, there are still many problems, such as how environmental changes affect the relationship between species diversity and plant functional traits, and how these interactions affect plant community functions. We examined the relationships among leaf and fine root functional traits, species diversity, and functional diversity at the community level, along with their environmental interpretations, in a plant community within the desert–oasis transition zone of the Hexi Corridor, where habitats are undergoing significant small-scale changes. During dune succession, plant community composition and diversity exhibited significant variation. Plants are adapted to environmental changes through synergistic combinations of above-ground and below-ground traits. Specifically, plants in fixed dunes adopted a “slow investment” strategy, while those in semi-fixed and mobile dunes employed a “fast investment” approach to resource acquisition. A strong coupling was observed between plant community functional traits and species diversity. Soil phosphorus content and compactness emerged as primary factors influencing differences in plant community functional traits and composition. These soil factors indirectly regulated fine root functional traits and diversity by affecting species diversity, thereby driving community succession. Our study elucidates the “soil—diversity—community functional trait” linkage mechanisms in the successional process of desert plants. This research provides scientific support for the restoring and reconstruction of degraded ecosystems in arid zones. Full article

The saiga antelope (Saiga tatarica), a keystone migratory species of the Central Asian steppes and deserts, is increasingly threatened by habitat fragmentation due to the rapidly expanding transport infrastructure in Kazakhstan, which hosts approximately 95% of the species’ global population. This study provides a spatial assessment of railway and road infrastructure across the contemporary ranges of the Betpaqdala, Ustyurt, and Ural saiga populations. Using the literature and our field data from the 1980s to the present day, combined with geographic information system (GIS)-based analysis of 80,427 km of roads and 4021 km of railways, we have quantified infrastructure densities and identified critical barriers to saiga migration using kernel density and minimum convex polygons (MCP) estimations. The results reveal a negative connection between infrastructure density and occurrences of saiga herds, particularly in the Ustyurt population, where a high railway density coincides with severely reduced migratory activity and a reduction in this population’s winter range by 79.84% since 2015. Major railways such as Sekseuildi–Zhezqazgan, Zhezqazgan–Zharyk, and Shalqar–Beineu intersect essential migratory pathways and have contributed to significant range contraction, subpopulation isolation, and northward shifts in seasonal habitats. In contrast, the Ural population (subject to minimal railway infrastructure interference) has shown robust demographic recovery. While roads are more widespread, their impact is less severe due to greater permeability. However, upcoming projects such as the China–Europe transit corridor and the “Center–West” regional development corridor could amplify future threats. We recommend immediately implementing wildlife-friendly infrastructure, including overpasses and ecological corridors, to preserve the connectivity of saiga ranges and support the long-term conservation of this ungulate species. Full article

This study employs a multi-model coupling and multi-scenario simulation approach to construct a framework for identifying and optimizing avian ecological corridors in the urban core of Kunming. The framework focuses on the ecological needs of resident birds (64.72%), woodland-dependent birds (39.87%), and low-mobility birds (47.29%) to address habitat fragmentation and enhance urban biodiversity conservation. This study identifies 54 core ecological corridors, totaling 183.58 km, primarily located in forest–urban transition zones. These corridors meet the continuous habitat requirements of resident and woodland-dependent birds, providing a stable environment for species. Additionally, 55 general corridors, spanning 537.30 km, focus on facilitating short-distance movements of low-mobility birds, enhancing habitat connectivity in urban fringe areas through ecological stepping stones. Eighteen ecological pinch points (total area 5.63 km²) play a crucial role in the network. The northern pinch points, dominated by forest land, serve as vital breeding and refuge habitats for woodland-dependent and resident birds. The southern pinch points, located in wetland-forest ecotones, function as critical stopover sites for low-mobility waterbirds. Degradation of these pinch points would significantly reduce available habitat for birds. The 27 ecological barrier points (total area 89.79 km²), characterized by urban land use, severely impede the movement of woodland-dependent birds and increase the migratory energy expenditure of low-mobility birds in agricultural areas. Following optimization, resistance to resident birds in core corridors is significantly reduced, and habitat utilization by generalist species in general corridors is markedly improved. Moreover, multi-scenario optimization measures, including the addition of ecological stepping stones, barrier improvement, and pinch-point protection, have effectively increased ecological sources, met avian habitat requirements, and secured migratory pathways for waterbirds. These measures validate the scientific rationale of a multidimensional management strategy. The comprehensive framework developed in this study, integrating species needs, corridor design, and spatial optimization, provides a replicable model for avian ecological corridor construction in subtropical montane cities. Future research may incorporate bird-tracking technologies to further validate corridor efficacy and explore planning pathways for climate-adaptive corridors. Full article

The continuous configuration changes and velocity variations of tilt-rotor UAVs during the transition phase pose significant challenges to flight safety. Hence, the transition phase trajectory must be specially designed. The transition corridor is an effective means of characterizing the controllable flight state and safe flight boundary of the tilt-rotor UAV transition phase. However, the conventional transition corridor is established based on the trim criterion, which cannot fully characterize the dynamic characteristics of the transition phase, resulting in deviations in the delineation of the flight boundary. This paper proposes a method that characterizes the dynamic transition corridor of a tilt-rotor UAV during the transition phase. A three-dimensional transition corridor considering the nacelle angle, velocity, and angle of attack is established by relaxing the force constraints and introducing angle of attack variables, allowing the dynamic characteristics of acceleration and deceleration in the transition phase to be characterized. On this basis, a transition trajectory optimization method based on the three-dimensional dynamic transition corridor is established using pigeon-inspired optimization with an objective that considers the smooth transition of tilt-rotor UAVs. Numerical simulations show that, compared with the transition trajectory obtained using a two-dimensional transition corridor, the proposed method ensures smoother changes in the velocity, nacelle angle, and expected angle of attack during the transition phase, resulting in stronger engineering practicality. Full article

International industrial transfer has driven rapid construction land expansion in emerging metropolitan areas, posing challenges for sustainable land management. However, existing research has largely overlooked the spatiotemporal patterns and driving mechanisms of this expansion, particularly in Southeast Asian metropolitan regions. To address this gap, we focused on the Ho Chi Minh City metropolitan area, utilizing construction land data from GLC_FCS30D to analyze the dynamics of construction land expansion during this period. Findings indicated that: (1) Continuous expansion of construction land, with the expansion rate during 2010–2020 being five times that of 2000–2010; (2) The spatial pattern evolved from initial infilling development in urban cores to subsequent leapfrogging and edge expansion toward peripheral counties and transportation corridors; (3) The expansion of construction land occurred alongside substantial losses of wetland and cultivated land. Between 2000 and 2020, the conversion of cultivated land to construction land increased significantly, particularly during 2010–2020 when cultivated land conversion accounted for 93.76% of newly developed construction land. Wetland conversion also showed notable growth during this period, comprising 3.86% of total newly added construction land; (4) Foreign direct investment (FDI) served as the primary catalyst, while industrial park development and transport infrastructure projects functioned as secondary accelerants. This study constructed a framework to systematically analyze the global and local driving mechanisms of metropolitan land expansion. The findings deepen the understanding of land-use transitions in emerging countries and provide both theoretical support and policy references for sustainable land management. Full article

Urban air pollution from potentially toxic elements (PTEs) presents a critical threat to public health and environmental sustainability. The current study employed Syntrichia moss in a passive biomonitoring capacity to ascertain the levels of atmospheric PTE pollution in Thessaloniki, Greece. A comprehensive collection of 192 moss samples was undertaken at 16 urban sampling points over the March–July 2024 period. Concentrations of 21 PTEs were quantified using ICP-MS, and contamination levels were assessed through contamination factor (CF), enrichment factor (EF), and pollution load index (PLI). Positive matrix factorization (PMF) modeling and multivariate statistical analyses were used to identify pollution sources and spatiotemporal variations. Results revealed persistent hotspots with significant anthropogenic enrichments of elements, such as Fe, Mn, Sn in industrial zones and Tl, Ce, Pt in traffic corridors. PMF modeling attributed 48% of the measured PTE variance to traffic-related sources, 35% to industrial sources, and 17% to crustal material. Seasonal transitions showed a significant 3.5-fold increase in Tl during summer, indicating elevated traffic-related emissions. This integrated multi-index and source apportionment framework demonstrates the efficacy of Syntrichia moss for high-resolution urban air quality assessment. The approach offers a cost-effective, scalable, and environmentally friendly tool to support EU-aligned air quality management strategies. Full article

A Transit-Oriented Development (TOD) strategy aims to reshape the spatial structure of high-density cities by encouraging the development of functional compounding and centralizing development goals. As a primary planning model, TOD station areas are based on zones’ structure. Studies have confirmed, however, that the current land structure between zones displays a high degree of homogeneity. There are several issues shown here, such as blurred station boundaries, spatial confusion, and a deviation of the TOD center. Based on the corridor effect theory, differentiated distribution characteristics of land structural elements are determined between zones. To clarify the difference between station zones, this study uses the floor area ratio attenuation rate as its primary method. As well as measuring their changes, it also measures their trends. The purpose of this study is to investigate the interactive relationship between multiple elements in the station zoning planning process. Also, it aims to explore the endogenous relationship of the station area with its existing spatial characteristics. Accordingly, a zoning planning model of 200–400–700 m is proposed, which lays the foundation for future research on standards for boundary delineation and center migration trajectory rules for station area zones. Full article

Background: The maritime industry is undergoing a profound transformation to meet global decarbonization goals. As Industry 4.0 advanced digital technologies are increasingly integrated into shipping operations, the role of the human element is evolving significantly. This intersection of decarbonization, digitalization, and human element/workforce transformation lays the foundation for more structured initiatives such as Green Digital Shipping Corridors (GDSCs), a strategic solution to scale zero-emission, smart maritime routes. Methods: This paper explores the interconnected roles of decarbonization, digitalization, and human capital development through a systematic literature review. It examines how these pillars converge in the implementation of GDSCs, drawing on academic and industry sources to identify challenges and opportunities in workforce readiness, policy integration, and technological adoption. Results: The findings underscore the necessity of coordinated action across the three pillars, particularly highlighting the importance of structured training programs, cross-sector collaboration, and standardized regulations. GDSCs are presented as an applied framework to align these transitions, enabling scalable, digitally enabled, low-emission maritime routes. Conclusions: There is a significant gap in current research that holistically connects the human factor with technological and environmental imperatives in the context of maritime transformation. This paper addresses that gap by introducing GDSCs as a strategic outcome of integrated change, providing actionable insights for policymakers, industry leaders, and educators aiming to advance sustainable shipping. Full article