Search Results (3,826)

This study collected 820 topsoil samples from cultivated lands across Ningxia, covering the Yellow River irrigation area, the central arid zone, and the southern mountainous region. The ordinary kriging were spatially interpolated to analyze As, Hg, Cd, Cr, and Pb heavy-metal pollution spatial patterns. Pollution was evaluated using the Nemerow and geoaccumulation (I_(geo)) indices, and sources quantified via Pearson correlations, PCA (Principal Component Analysis), and PMF (Positive Matrix Factorization). The results indicated that Hg and Cd posed the highest ecological risks. The overall mean concentrations (mg.kg⁻¹) of Hg, Cd, As, Pb, and Cr were 0.04, 0.27, 9.91,23.81, and 57.34, respectively. Compared with the background values, they were 1.90, 2.41, 0.83, 1.14, 2.74 times higher, respectively. Geospatially, regions with higher pollution probabilities for Cd, Cr, Pb, Hg, and As were concentrated in the northern and central parts of Ningxia, whereas the southern region exhibited lower pollution probabilities. pH significantly influenced the accumulation and spatial distribution of heavy metals in soil. Source apportionment identified three primary contributors: transportation and natural parent materials (As, Pb, Cr), industrial activities (Hg), and agricultural practices (Cd). Hg and Cd were identified as the key risk elements requiring prioritized management. These results enhance understanding of the pollution levers of heavy metals in Ningxia cultivated soils, and also provide foundation for developing more scientific and precise soil risk control policies, offering significant practical value for environmental risk management. Full article

This study investigates spatiotemporal b value variations and seismic interaction networks preceding the M_wg 7.1 Dingri earthquake that struck southern Tibet on 7 January 2025. Using relocated earthquake catalogs (2021–2025) and dual-method analysis combining b value mapping with Granger causality network modeling, we reveal systematic precursory patterns. Spatial analysis shows that the most significant b value reduction (Δb > 0.5) occurred north of the mainshock epicenter at seismogenic depths (5–15 km), closely aligning with subsequent aftershock concentration zones. Granger causality analysis reveals a progressive network simplification: from 73 causal links among 28 nodes during the background period (2021–2023) to 49 links among 34 nodes pre-mainshock (2023–2025) and finally to 6 localized links post-rupture. This transition from distributed system-wide interactions to localized “locked-in” dynamics reflects the stress concentration onto the primary asperity approaching critical failure. The convergence of b value anomalies and network evolution provides a comprehensive framework linking quasi-static stress states with dynamic system behavior. These findings offer valuable insights for understanding earthquake nucleation processes and improving seismic hazard assessment in the Tibetan Plateau and similar complex tectonic environments. Full article

PM_2.5 is the primary source of urban atmospheric pollution, as it not only damages the ecological environment but also poses a threat to human health. Taking the Yangtze River Economic Belt as the research object, this study analyzes the spatiotemporal variation characteristics of PM_2.5 concentrations in the region from 2005 to 2020. Furthermore, by combining the Geodetector model with Geographically and Temporally Weighted Regression (GTWR) model, the spatiotemporal heterogeneity of its influencing factors is revealed at three scales: municipal, watershed, and grid. The results show that, from 2005 to 2020, the annual average PM_2.5 concentration in the Yangtze River Economic Belt exhibited an inverted U-shaped trend with 2013 as the inflection point, showing distinct spatial clustering characteristics. Overall, the spatiotemporal variation in annual average PM_2.5 concentration demonstrated a significant downward trend during this period, with slower decline rates in the western region and faster rates in the central and eastern regions. Spatial differentiation of annual average PM_2.5 concentrations within the region was primarily influenced by three factors: PFA, PISA, and PD. NDVI and PWA exerted their effects mainly at large scales, while MAT and SDE primarily acted at small scales. Within the region, NDVI and CVO predominantly suppressed PM_2.5 concentrations, whereas MAT, PFA, PD, and SDE primarily promoted PM_2.5 pollution. The spatial distribution of effects for factors within the same category is broadly consistent across the three scales, though details vary. This study overcomes previous limitations of administrative-scale research, yielding more refined results. It provides new methodologies and insights for future research while offering more precise scientific support for regional PM_2.5 governance. Full article

As tourism increasingly drives the revitalization of traditional villages, rural spaces are undergoing a transformation from functional living areas to spaces for cultural display and leisure. This shift has amplified the spatial usage discrepancies between multiple stakeholders, such as tourists and villagers, highlighting conflicts in spatial resource allocation and behavior path organization. Using Wulin Village, a typical example of a Minnan overseas Chinese village, as a case study, this paper introduces social network analysis to construct a “spatial–behavioral” dual network model. The model integrates both architectural and public spaces, alongside behavior path data from villagers and tourists, to analyze the spatial structure at three scales: village-level network completeness, district-level structural balance, and point-level node vulnerability. The study integrates two dimensions—architectural space and public space—along with behavioral path data from both villagers and tourists. It reveals the characteristics of spatial structure under the intervention of multiple behavioral agents from three scales: village-level network completeness, district-level structural balance, and point-level node vulnerability. The core research focus of the spatial network includes the network structure of architectural and public spaces, while the behavioral network concerns the activity paths and behavior patterns of tourists and villagers. The study finds that, at the village scale, Wulin Village’s spatial network demonstrates good connectivity and structural integrity, but the behavior paths of both tourists and villagers are highly concentrated in core areas, leading to underutilization of peripheral spaces. This creates an asymmetry characterized by “structural integrity—concentrated behavioral usage.” At the district scale, the spatial node distribution appears balanced, but tourist behavior paths are concentrated around cultural nodes, such as the ancestral hall, visitor center, and theater, while other areas remain inactive. At the point scale, both tourist and villager activities are highly dependent on a few high-degree, high-cluster nodes, improving local efficiency but exacerbating systemic vulnerability. Comparison with domestic and international studies on cultural settlements shows that tourism often leads to over-concentration of spatial paths and node overload, revealing significant discrepancies between spatial integration and behavioral usage. In response, this study proposes multi-scale spatial optimization strategies: enhancing accessibility and path redundancy in non-core areas at the village scale; guiding behavior distribution towards multifunctional nodes at the district scale; and strengthening the capacity and resilience of core nodes at the point scale. The results not only extend the application of behavioral network methods in spatial structure research but also provide theoretical insights and practical strategies for spatial governance and cultural continuity in tourism-driven cultural villages. Full article

A notable decline in the frequency of sea fog inflows and an increase in low-cloud ceiling height were observed following the construction of the Saemangeum Seawall west of the Gunsan Airport, an area traditionally prone to frequent sea fog events. To the mechanisms underlying these changes, a numerical experiment was conducted using the Weather Research and Forecasting model. An 11-m-high seawall was used as a physical barrier, and an elevated sea surface temperature (SST) was established within the enclosed area to simulate realistic post-construction conditions. The model successfully reconstructed sea fog occurrences, and the cloud–water mixing ratio effectively captured the spatial distribution of sea fog. Deviations from the control experiment showed a consistent pattern of reduced cloud–water mixing ratios near the surface and enhanced concentrations at high levels. Decreased buoyancy frequency in the surface layer enhanced atmospheric instability, inducing upward motion and intensified condensation activity. Increases in the turbulence kinetic energy within the planetary boundary layer (TKE within the PBL), vertical wind shear, and temperature further corroborated the reduction in sea fog and enhanced stratus formation. These findings indicate that the increased SST and seawall significantly influence the modification of the sea fog structure and its inflow dynamics. Full article

Cultural ecosystem services (CES) represent fundamental expressions of human-environment interactions. A comprehensive assessment of CES supply and demand offers a robust scientific foundation for optimizing the transformation of ecosystem service values to improve human well-being. This study integrates multi-source datasets and employs Maximum Entropy (MaxEnt) modeling with the ArcGIS platform to analyze the spatial distribution of CES supply and demand in Hunan Province, a typical mountain tourism regions in China. Furthermore, geographical detector methods were used to identify and quantify the driving factors influencing these spatial patterns. The findings reveal that: (1) Both CES supply and demand demonstrate pronounced spatial heterogeneity. High-demand areas are predominantly concentrated around prominent scenic locations, forming a “multi-core, clustered” pattern, whereas high-supply areas are primarily located in urban centers, water systems, and mountainous regions, exhibiting a gradient decline along transportation corridors and river networks. (2) According to the CES supply-demand pattern, Hunan Province can be classified into demand, coordination, and enhancement zones. Coordination zones dominate (45–70%), followed by demand zones (20–30%), while enhancement zones account for the smallest proportion (5–20%). (3) Urbanization intensity and land use emerged as the primary drivers of CES supply-demand alignment, followed by vegetation cover, distance to water bodies, and population density. (4) The explanatory power of two-factor interactions across all eight CES categories surpasses that of any individual factor, highlighting the critical role of synergistic multi-factorial influences in shaping the spatial pattern of CES. This study provides a systematic analysis of the categories and driving factors underlying the spatial alignment between CES supply and demand in Hunan Province. The findings offer a scientific foundation for the preservation of ecological and cultural values and the optimization of spatial patterns in mountain tourist areas, while also serving as a valuable reference for the large-scale quantitative assessment of cultural ecosystem services. Full article

The aim of this study was to rigorously quantify and analyse the concentrations of atmospheric pollutants (PM₁₀, PM_2.5, SO₂, NO₂, CO, H₂S, and O₃) emitted by artisanal brick kilns in Juliaca City, Peru. The AERMOD dispersion model and a network of low-cost sensors (LCSs) were employed to characterise air quality at specific receptor sites. A georeferenced inventory of kiln operations was created to determine their parameters and operational intensity, providing a foundation for estimating emission factors and rates. Data were obtained from the United States Environmental Protection Agency (EPA) and supplemented with locally gathered meteorological records, which were processed for integration into the AERMOD model. The findings revealed that brick kilns are a principal source of atmospheric pollution in the region, with carbon monoxide (CO) emissions being especially pronounced. The LCSs facilitated the identification of pollutant concentrations at various locations and enabled the quantification of the specific contribution of brick production to ambient aerosol levels. Comparative assessments determined that these sources account for approximately 85% of CO emissions within the study area, underscoring a significant adverse impact on air quality and public health. Background pollutant levels, emission rates, spatial distributions, and concentration patterns were analysed within the assessment zones, resulting in solid model performance. These results provide a sound scientific basis for the formulation and implementation of targeted environmental mitigation policies in urban areas and the outskirts of Juliaca. Full article

We develop a new mathematical framework for describing impurity diffusion in multiphase, stochastically inhomogeneous media with internal deterministic mass sources. The main contribution of the paper is the structural preservation of the original multiphase problem while reducing it to a single integro-differential diffusion equation for the entire body. Using a Feynman diagram technique, we obtain a Dyson-type equation for the averaged concentration field; its kernel (mass operator) summarizes the cumulative effect of random phase interfaces and internal sources. This diagrammatic formulation offers clear advantages: it systematically organizes the contributions of complex interphase interactions and source terms, ensures convergence of the Neumann-series solution, and facilitates extensions to more intricate source distributions. The approach allows us to analyze the behavior of the averaged impurity concentration under various temporally or spatially distributed internal sources and provides a foundation for further refinement of transport models in complex multiphase systems. Full article

To investigate the influence mechanism of hanger damage and arch-beam combined parameters on the failure behavior of tied-arch bridges, this study employs an advanced damage failure model within the LS-DYNA. A comprehensive simulation of the entire failure process was conducted, considering the coupled effects of hanger damage parameters and structural parameters of the arch-beam system, using a tied-arch bridge as the engineering case. The primary innovation of this study lies in overcoming the limitations of previous research, which has largely been confined to single hanger failure or static parameter analysis, by achieving, for the first time, dynamic tracking and quantitative identification of structural failure paths under the coupled influence of multiple parameters. The results demonstrate that both the severity and spatial distribution pattern of hanger damage significantly influence the structural failure mechanism. When damage is either uniformly distributed across the bridge or relatively concentrated—particularly when long hangers experience severe degradation—the structure becomes susceptible to cascading stress redistribution, substantially increasing the risk of global progressive collapse. This finding provides a theoretical foundation for developing risk-informed maintenance and repair strategies for hangers. It is therefore recommended that practical maintenance efforts prioritize monitoring the condition of long hangers and regions with concentrated damage. Furthermore, variations in arch-beam combined parameters are shown to have a significant effect on the structure’s collapse resistance. For the case bridge studied herein, the original design parameters achieve an optimal balance between anti-collapse performance and economic efficiency, underscoring the importance of rational parameter selection in enhancing system robustness. This work offers both theoretical insights and numerical tools for evaluating and optimizing the collapse-resistant performance of under-deck tied-arch bridges, contributing meaningful engineering value toward improving the safety and durability of similar structures. Full article

As an important part of the urban ecological environment, urban green space plays a crucial and irreplaceable role in improving air quality, promoting sustainable development, and enhancing residents’ quality of life. This study takes Beijing’s urban green space as the research object. Based on Landsat series satellite remote sensing images, the land use distribution of Beijing is obtained through supervised classification. Combined with data such as PM_2.5 concentration and wind speed, the dry deposition efficiency of PM_2.5 is quantitatively analyzed. The results show that: (1) Beijing’s urban green space has significant advantages in PM_2.5 dry deposition. In terms of dry deposition flux, the order of annual average deposition of different land types is: forest land > farm land > grassland > impervious surface > water body = unutilized land. Among them, forest land has the best dry deposition effect, with an annual average dry deposition of 1.13 g/m², which is 188.41 times that of impervious surface; cultivated land and grassland are 0.22 g/m² and 0.19 g/m² respectively, which are 37.13 times and 32.34 times that of impervious surface. (2) From 2000 to 2020, the PM_2.5 removal rate of green space continued to rise, but the reduction amount showed a trend of first increasing and then decreasing. There are significant seasonal differences. The reduction amount is the highest in autumn (reaching 449.90 tons in October), followed by summer, spring, and winter (the lowest in August, at 190.27 tons). (3) In terms of spatial distribution, the high-value areas of dry deposition are concentrated in the suburbs, showing a “southwest-northeast” axial distribution, while the low-value areas are mainly located in the outer suburbs, reflecting the imbalance of green space layout and the regional differences in PM_2.5 reduction. Combined with the current situation of green space in Beijing, the study puts forward targeted optimization suggestions, providing theoretical support and scientific basis for the construction of Beijing as a “garden city”. Full article

This study investigates the spatial distribution of the hydromagnesite (HM) mineral in Akgöl, a closed basin located in the arid southwestern region of Türkiye, through the integration of geochemical analyses and remote sensing techniques. A total of 70 sediment samples were analyzed using X-ray Fluorescence (XRF), X-ray Diffraction (XRD), and spectroradiometry to determine their mineralogical composition. The resulting data were integrated with ASTER satellite imagery, and mineral distribution maps were generated across 13,293 pixels using multiple linear regression and Kriging interpolation techniques within the ArcGIS environment. The findings indicate that hydromagnesite is predominantly concentrated in the central part of the lake, where it represents the dominant mineral phase in contrast to lower concentrations observed along the periphery. The endorheic nature of Akgöl is comparable to other saline lakes with similar geological and climatic settings, such as Salda and Acıgöl, supporting the applicability of this methodological approach to mineral exploration in other arid and semi-arid environments. The study contributes not only to the regional assessment of mineral potential but also to the advancement of remote sensing and GIS-based analytical methods in geoscientific research. Full article

Understanding sediment transport under varying flow regimes and its associated scouring–silting responses is fundamental for analyzing the coupled dynamics of hydrology and river morphology. However, in large alluvial rivers strongly modified by human interventions such as dam operations, identifying critical thresholds of scouring–silting transitions remains a major challenge. This study examines sediment transport dynamics and flow frequency patterns through statistical analysis and the coefficient of determination method, using daily discharge and suspended sediment concentration records from eight hydrological stations along the middle and lower Yangtze River, China, covering 1990–2023. The results demonstrate that the impoundment of the Three Gorges Reservoir substantially altered downstream hydrological and sediment regimes, leading to a more uniform flow frequency distribution, suppression of extreme flows, and increased prevalence of moderate discharges. These adjustments stabilized river flows and improved sediment transport efficiency. Distinct spatial variations were identified across seven river sections: upstream reaches shifted from bimodal scouring–silting patterns to scouring-dominated regimes, whereas downstream reaches exhibited weakened sediment deposition. Moreover, critical thresholds of both flow and sediment coefficients displayed systematic longitudinal shifts. Collectively, these findings provide new insights into water–sediment interactions under large-scale regulation and offer practical implications for sediment management in highly engineered river systems. Full article

This study provides the first integrated spatio-temporal assessment of water quality in Lakes Tonga and Oubeira, two adjacent Ramsar-designated wetlands within El Kala National Park (Algeria). The objective was to identify major pollution sources and inform targeted conservation strategies. Physico-chemical, microbiological, and heavy metal analyses were performed on water samples collected monthly over one year (September 2022–August 2023) from two sites per lake. Applying robust statistical analyses (ANOVA, Kruskal–Wallis, PCA, boxplots) and high-resolution spatial mapping, we revealed significant spatio-temporal heterogeneity and distinct pollution profiles between the two lakes. Specifically, Lake Tonga exhibited higher concentrations of organic and bacterial pollutants, likely linked to agricultural runoff and domestic discharge, while Lake Oubeira was characterized by elevated heavy metal concentrations and higher mineralization. The calculated Water Quality Index (WQI) classified the water quality of both lakes predominantly as “Moderate”, with punctual “Poor” quality episodes. Numerous parameters consistently exceeded water quality standards, indicating substantial ecological and health risks. Spatial distribution maps clearly pinpointed pollution hotspots, guiding lake-specific management measures. These findings underscore the urgent need for differentiated, targeted management interventions and an integrated, multidisciplinary approach for the effective conservation of these valuable wetland ecosystems. Full article

Monitoring nitrate levels in water is critical to protect public health and ensure compliance with regulatory standards. This study provides a comprehensive evaluation of four analytical techniques—test strips, ion-selective electrodes (ISE), colorimetric methods, and titration—to assess nitrate levels in a variety of water sources, including standard solutions, rainwater, bottled water, and groundwater from both shallow and deep wells located in semi-urban regions of Saudi Arabia. Each method was assessed for sensitivity, accuracy, detection limits, reproducibility, and operational practicality. Test strips offer rapid, low-cost screening but consistently underestimate nitrate concentrations, particularly at low levels. The ISE demonstrated broad applicability and reliable performance across a wide concentration range when properly calibrated, making it suitable for both field and laboratory applications. Colorimetric methods provide excellent sensitivity for trace-level detection, whereas titration delivers the highest accuracy for high-nitrate samples despite its time-intensive nature. By calibrating and validating the methods against certified standards, we quantitatively demonstrated their reliability through statistical measures such as precision and accuracy rates. Moreover, the application of Geographic Information System (GIS) techniques in spatial analysis has revealed significant differences in the distribution of nitrates. Notably, shallow wells located in the northern regions surpass the 50 mg/L limit set by the World Health Organization (WHO), thereby indicating the presence of localized contamination hotspots. This study is among the first to systematically compare nitrate detection methods across a wide range of water types in a semi-urban area of Saudi Arabia. Building on a detailed analysis of each method, we underline the crucial need for the strategic selection of nitrate analysis techniques. This selection should be tailored to specific operational contexts, accuracy requirements, and concentration ranges to guide stakeholders towards more informed decision-making. These findings provide actionable guidance for public health officials and water managers to prioritize monitoring, safeguard drinking-water sources, and mitigate nitrate-related health risks in semi-urban communities. Full article

Climate change poses growing threats to Amazonian biodiversity, yet species-specific responses remain poorly understood, particularly in the Colombian Amazon. This study assessed the potential distribution and habitat suitability of eight woody plant species—Euterpe precatoria (Mart.) A.J.Hend., Mauritia flexuosa L.f., Oenocarpus bataua Mart., Minquartia guianensis Aubl., Cedrela odorata L., Virola elongata (Benth.) Warb., Theobroma grandiflorum (Willd. ex Spreng.) Schum. and Thebroma cacao L.—under a baseline period (1970–2000) and future climate projections for mid- (2041–2060) and late-century (2061–2080) periods, using two Shared Socioeconomic Pathways (SSP245 and SSP585). Species distribution models (SDMs) integrated bioclimatic, edaphic, and topographic predictors and were spatially intersected with Special Management Areas. Results revealed contrasting responses among species. M. flexuosa, E. precatoria, O. bataua, V. elongata, M. guianensis and T. cacao retained over 95% of their baseline suitable habitat and even expanded into new regions, reflecting broad climatic resilience under both future scenarios. In contrast, C. odorata experienced moderate contractions, losing 8.7% of their current ranges under SSP585 by 2080. The most vulnerable species was T. grandiflorum, projected to lose up to 27% of its current suitable habitat under the most pessimistic scenario. Overall, losses were mainly concentrated in the natural fractions of Indigenous Reserves and National Natural Parks. These findings underscore the heterogeneous responses of Amazonian species to climate change and highlight the need for adaptive conservation and management strategies. Protecting climate refugia, promoting ecological connectivity, and incorporating climate-resilient species into restoration programs will be critical to maintaining biodiversity, ecosystem services, and local livelihoods in the Colombian Amazon under future climates. Full article