Search Results (224)

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

The river source region of the Yellow River Basin is a critical ecological barrier in China, yet it is characterized by extreme environmental vulnerability. Human activities, particularly intensive mining, can severely disrupt the landscape ecosystem and alter its spatial patterns. The aim of this study is to conduct a comprehensive landscape ecological risk assessment, analyzing the spatial differentiation and driving factors of these risks to ensure regional ecological security. Employing high-resolution remote sensing technology, a comprehensive assessment of landscape ecological risk in the river source region of the Yellow River Basin was conducted based on the 2020 mining development status. The landscape ecological risk index (ERI_k) was applied to evaluate risk distribution patterns, while the Geodetector model implemented in R was utilized to identify and analyze key driving factors. The results were as follows: (1) The study area exhibited an elevated landscape ecological risk. (2) Anthropogenic disturbances, such as urban construction, residential activities, and mining, combined with a widespread cropland distribution, degraded alpine grasslands, and high landscape fragility, were identified as major contributors to the elevated landscape ecological risk in the study area. (3) Habitat quality and population density remain the most significant factors driving the spatial differentiation of landscape ecological risk, and their interaction strongly governs the spatial distribution of such risk. In contrast, mining development intensity is not a dominant factor influencing the spatial heterogeneity of landscape ecological risk at the regional scale in the study area. This assessment reveals the extent of ecological risk associated with mining and other human activities and its key drivers. Full article

Water conservation, as a critical ecosystem service, plays a vital role in maintaining regional water resources balance. Against the backdrop of rapid urbanization, the expansion of construction land has intensified the encroachment on ecological spaces, posing significant challenges to water resource carrying capacity. From a supply–demand perspective, this study employs the InVEST model and integrates multi-source data including meteorological and socio-economic datasets to construct models of water conservation supply and demand. Furthermore, spatial analysis methods are applied to examine the evolution of water resource carrying capacity in Gansu Province—a key region within the Yellow River Basin—from 2000 to 2020. The results indicate the following: (1) through desertification control, unused land has been progressively restored to grassland, yet continuous urban expansion has substantially encroached upon surrounding plowland and grassland; (2) the spatial pattern of water conservation supply exhibits a “high in the south and west, low in the north and east” distribution, with the maximum value per pixel increasing from 7.89 × 10⁵ m³ to 8.15 × 10⁵ m³. Overall, water resource carrying capacity has generally declined, with intensified pressure in central cities such as Lanzhou, while some improvement is observed in forested areas of the south; and (3) cold spots in the western Qilian Mountains have expanded toward the Hexi Corridor, reflecting significant spatial changes and indicating ecological degradation. Urbanization has markedly exacerbated regional imbalances in water resource carrying capacity, providing a scientific basis for water–ecological risk management in arid regions. Full article

The dynamic changes in vegetation significantly impact the sustainability, safety, and stability of ecosystems in the source region of the Yellow River. However, the spatiotemporal patterns and driving factors of these changes remain unclear. The MODIS NDVI dataset (1998–2018), together with climatic records from meteorological stations and socio-economic statistics, was collected to investigate the spatiotemporal characteristics of vegetation coverage in the study area. For the analysis, we employed linear trend analysis to assess long-term changes, Pearson correlation analysis to examine the relationships between vegetation dynamics and climatic as well as anthropogenic factors, and t-tests to evaluate the statistical significance of the results. The results indicated the following: (1) From 1998 to 2018, vegetation in the source region of the Yellow River generally exhibited an increasing trend, with 92.7% of the area showed improvement, while only 7.3% experienced degradation. The greatest vegetation increase occurred in areas with elevations of 3250–3750 m, whereas vegetation decline was mainly concentrated in regions with elevations of 5250–6250 m. (2) Seasonal differences in vegetation trends were observed, with significant increases in spring, summer, and winter, and a non-significant decrease in autumn. Vegetation degradation in summer and autumn remains a concern, primarily in southeastern and lower-elevation areas, affecting 25% and 27% of the total area, respectively. The maximum annual average NDVI was 0.70, occurring in 2018, while the minimum value was 0.59, observed in 2003. (3) Strong correlations were observed between vegetation dynamics and climatic variables, with temperature and precipitation showing significant positive correlations with vegetation (r = 0.66 and 0.60, respectively; p < 0.01, t-test), suggesting that increases in temperature and precipitation serve as primary drivers for vegetation improvement. (4) Anthropogenic factors, particularly overgrazing and rapid population growth (both human and livestock), were identified as major contributors to the degradation of low-altitude alpine grasslands during summer and autumn periods, with notable impacts observed in counties with higher livestock density and population growth, indicating that for each unit increase in population trend, the NDVI trend decreases by an average of 0.0001. The findings of this research are expected to inform the design and implementation of targeted ecological conservation and restoration strategies in the source region of the Yellow River, such as optimizing land-use planning, guiding reforestation and grassland management efforts, and establishing region-specific policies to mitigate the impacts of climate change and human activities on vegetation ecosystems. Full article

This study investigates the interaction between digital–intelligent integration and carbon productivity in 23 prefecture-level cities across the middle reaches of the Yellow River from 2013 to 2022, focusing on a resource-dependent region transitioning towards low-carbon development. The aim is to examine how digital technologies contribute to improving carbon productivity and reducing environmental pollution. An entropy-weighted index system was used to assess digital–intelligent transformation and carbon productivity. A coupling coordination model was applied to measure their joint performance, with spatial autocorrelation and spillover analyses used to detect regional patterns and intercity linkages. Data were sourced from official yearbooks, environmental bulletins, and urban big-data platforms. The results show a steady improvement in coordination between digital–intelligent integration and carbon productivity, with significant progress in 2018 and 2020 following national policy initiatives. Core cities showed higher coordination and generated positive spillovers, while peripheral cities lagged, resulting in noticeable spatial agglomeration. These findings highlight the growing coupling between digital–intelligent development and carbon productivity, reinforced by policy initiatives but accompanied by regional disparities. This study suggests that policies should focus on enhancing data infrastructure in core cities, improving regional cooperation, and bridging gaps in peripheral areas. It offers insights into the role of digital technologies in achieving low-carbon development in resource-dependent urban regions. Full article

The Yellow River Delta is one of China’s most ecologically fragile regions, experiencing prolonged pressures from rapid urbanization and ecological degradation. Existing research, however, has predominantly focused on constructing ecological security patterns under single scenarios, with limited systematic multi-scenario comparisons and insufficient statistical support. To address this gap, this study proposes an integrated framework of “land use simulation—multi-scenario ecological security pattern construction—statistical comparative analysis.” Using the PLUS model, three scenarios were constructed—Business-as-Usual (BAU), Priority Urban Development (PUD), and Priority Ecological Protection (PEP)—to simulate land use changes by 2040. Habitat quality assessment, Multi-Scale Pattern Analysis (MSPA), landscape connectivity, and circuit theory were integrated to identify ecological source areas, corridors, and nodes, incorporating a novel hexagonal grid partitioning method. Statistical significance was evaluated using parametric tests (ANOVA, t-test) and non-parametric tests (permutation test, PERMANOVA). Analysis indicated significant differences in ecological security patterns across scenarios. Under the PEP scenario, ecological source areas reached 3580.42 km² (12.39% of the total Yellow River Delta), corresponding to a 14.85% increase relative to the BAU scenario and a 32.79% increase relative to the PUD scenario. These gains are primarily attributable to stringent wetland and forestland protection policies, which successfully limited the encroachment of construction land into ecological space. Habitat quality and connectivity markedly improved, resulting in the highest ecosystem stability. By contrast, the PUD scenario experienced an 851.46 km² expansion of construction land, resulting in the shrinkage of ecological source areas and intensified fragmentation, consequently increasing ecological security risks. The BAU scenario demonstrated moderate outcomes, with a moderately balanced spatial configuration. In conclusion, this study introduces an ecological restoration strategy of “five zones, one belt, one center, and multiple corridors” based on multi-scenario ecological security patterns. This provides a scientific foundation for ecological restoration and territorial spatial planning in the Yellow River Delta, while the proposed multi-scenario statistical comparison method provides a replicable methodological framework for ecological security pattern research in other delta regions. Full article

The Huangshui River Basin is located in the transition zone between the Loess Plateau and the Qinghai–Tibet Plateau, characterized by a fragile hydrological and ecological environment. Groundwater serves as a vital water source for local economic development and human livelihood. With the acceleration of urbanisation and climate change, groundwater resources face challenges such as pollution and over-exploitation. This study employs an improved DRASTIC model, tailored to the characteristics of the groundwater system in the Huangshui River Valley of the upper Yellow River, to integrate groundwater resources, groundwater environment, and ecological environment systems. Improving the DRASTIC model for groundwater vulnerability assessment. A two-tiered evaluation system with nine indicator parameters was proposed, including six groundwater quality vulnerability indicators and five groundwater quantity vulnerability indicators. Fuzzy analytic hierarchy process and entropy weight method were used to determine the weights, and Geographic Information System (GIS) spatial analysis was employed to evaluate groundwater vulnerability in the Huangshui River basin in 2006 and 2021. The results indicate that the proportion of areas with high groundwater quality vulnerability increased from 10.7% in 2006 to 31.57% in 2021, while the proportion of areas with high groundwater quantity vulnerability decreased from 22.33% to 14.02%. Overall, groundwater quality vulnerability in the Huangshui River basin is increasing, while groundwater quantity vulnerability is decreasing. Based on the evaluation results of water quality and quantity vulnerability, protection zoning maps for water quality and quantity were compiled, and preventive measures and recommendations for water quality and quantity protection zones were proposed. Human activities have a significant impact on groundwater vulnerability, with land use types and groundwater extraction coefficients having the highest weights. This study provides a scientific basis for the protection and sustainable use of groundwater in the Huangshui River basin. Full article

Agricultural soils near industrial parks in the Yellow River bend region face severe heavy metal pollution, posing a significant to human health. This study integrated field sampling with laboratory analysis and applied geostatistical analysis, positive matrix factorization (PMF) modeling, and health risk assessment models to systematically investigate the pollution levels, spatial distribution, sources, and ecological health risks of heavy metals in the area. The main findings are as follows: (1) The average concentrations of the eight heavy metals (Hg, Cr, Cu, Pb, Zn, As, Cd, and Ni) in the study area were 0.04, 48.3, 54.3, 45.7, 70.0, 22.9, 0.4, and 35.7 mg·kg⁻¹, respectively. The concentrations exceeded local background values by factors ranging from 1.32 to 11.2. Exceedances of soil screening and control values were particularly pronounced for Cd and As. Based on the geoaccumulation index, over 75% of the sampling sites for Cr, Pb, Zn, and Cd were classified as moderately to heavily polluted. Potential ecological risk assessment highlighted Cd as the significant ecological risk factor, indicating considerable heavy metal pollution in the region. (2) Kriging interpolation demonstrated elevated concentrations in the western (mid-upper) and eastern (mid-lower) subregions. Pearson correlation analysis suggested common sources for Cu-Pb-As-Cd and Cr-Zn-Ni. (3) PMF source apportionment identified four primary sources: traffic emissions (38.19%), natural and agricultural mixed sources (34.55%), metal smelting (17.61%), and atmospheric deposition (10.10%). (4) Health risk assessment indicated that the non-carcinogenic risk for both adults and children was within acceptable limits (adults: 0.065; children: 0.12). Carcinogenic risks were also acceptable (adults: 5.67 × 10⁻⁵; children: 6.70 × 10⁻⁵). In conclusion, priority should be given to the control of traffic emissions and agriculturally derived sources in the management of soil heavy metal contamination in this region, while the considerable contribution of smelting activities warrants heightened attention. This study provides a scientific basis for the prevention, control, and targeted remediation of regional soil heavy metal pollution. Full article

Groundwater is a vital water source for human survival and regulates the hydrological cycle within the uppermost strata. Through the processes of recharge and discharge, as well as solute exchange, it interacts with surface water systems in Zhengzhou, e.g., the Yellow River and the Jialu River. Therefore, systematically assessing its hydrochemical characteristics, driving factors, and health risks is crucial for ensuring the safety of public drinking water and regional development. This study focuses on shallow (45~55 m), medium-deep (80~350 m), deep (350~800 m), and ultra-deep (800~1200 m) groundwater in Zhengzhou City. A descriptive statistical analysis was employed to identify the primary chemical constituents of groundwater at various depths within the study area. Piper diagrams and the Shukarev classification method were employed to determine the hydrochemical types of the groundwater. Additionally, Gibbs diagrams, correlation coefficient methods, ion ratio coefficient methods and chlorine–alkali indices were employed to investigate the formation mechanisms of the chemical components of the groundwater, and the health risks in the study area were evaluated. Results: Ca²⁺ dominates the shallow/medium-deep groundwater, Na⁺ dominates the deep/ultra-deep groundwater; HCO₃⁻ (70~82%) is the dominant anion. Water chemistry shifts from HCO₃-Ca to HCO₃-Na with depth. Solubilisation, cation exchange, counter-cation exchange, and mixed processes primarily govern the formation of the groundwater’s chemical composition in the study area. Nitrate health risk assessments indicate significant differences in non-carcinogenic risks across four population groups (infants, children, young adults, and adults). Medium-depth groundwater poses a potential risk to all groups, while shallow and deep groundwater threaten only infants. Ultra-deep groundwater carries the lowest risk. Full article

The quantitative assessment of acoustic rain enhancement technology is highly significant for improving the ecological environment. A scientific and accurate evaluation of its operational effects provides an important basis for continued government and public support and investment in artificial weather modification activities. To effectively analyze the effects of acoustic rain enhancement on the vegetation of grassland ecosystems in arid and semi-arid areas and to clarify its mechanism, this study constructed eight vegetation indices based on Sentinel-2 satellite data. A comprehensive assessment of the changes in vegetation within the grassland ecosystem of the experimental zone was conducted by analyzing spatiotemporal distribution patterns, double-ratio analysis, and difference value comparisons. The results showed that (1) following the acoustic rain enhancement experiment, vegetation growth improved significantly. The mean values of all eight vegetation indices increased more substantially than before the experiment, with kNDVI showing the most notable gain. The proportion of the zone with kNDVI values greater than 0.417 increased from 52.62% to 71.59%, representing a relative increase of 36.05%. (2) The rain enhancement experiment significantly raised the values of eight vegetation indices: kNDVI increased by 0.042 (18.68%), ARVI by 0.043 (18.67%), and the remaining indices also increased to varying degrees (9.51–12.34%). (3) Vegetation improvement was more pronounced in areas closer to the acoustic rain enhancement site. Under consistent climate conditions, vegetation growth in the experimental zone showed significant enhancement. This study demonstrates that acoustic rain enhancement technology can mitigate drought and low rainfall, improve grassland ecosystem services, and provide a valuable foundation for ecological restoration and aerial water resource utilization in arid and semi-arid regions. Full article

The Source Region of the Yangtze and Yellow Rivers (SRYY), situated on the Qinghai-Tibet Plateau, serves as a vital ecological barrier and a critical component of the global carbon cycle. However, this region faces severe ecosystem degradation driven by climate change and human activities. This study establishes an integrated ecological security assessment framework that couples ecological risk, ecosystem health, and ecosystem services to evaluate ecological dynamics in the SRYY from 2000 to 2020. Leveraging multi-source data (vegetation, hydrological, meteorological) and advanced modeling techniques (spatial statistics, geographically weighted regression), we demonstrate that: (1) The Ecological Security Index (ESI) exhibited an initial increase followed by a significant decline after 2010, falling below its 2000 level by 2020. (2) The rising Ecological Risk Index (ERI) directly weakened both the ESI and Ecosystem Service Index (ESsI), with this negative effect intensifying markedly post-2010. (3) A distinct spatial gradient pattern emerged, shifting from high-security core areas in the east to low-security zones in the west, closely aligned with terrain and elevation; conversely, areas exhibiting abrupt ESI changes showed little correlation with permafrost degradation zones. (4) Vegetation coverage emerged as the key driver of ESI spatial heterogeneity, acting as the central hub in the synergistic regulation of ecological security by climate and topographic factors. Full article

Ecotourism is vital for harmonious human–nature coexistence in national parks, making the quantification of its spatial suitability an urgent scientific priority. This study took the Yellow River Estuary National Park (YRENP) as the study area and constructed a multi-criteria evaluation model by interpreting the relationship between Ecotourism Environmental Carrying Capacity (EECC) and Ecotourism Development Suitability (EDS), addressing the critical gap in the integrated land–sea ecotourism suitability assessment for coastal national parks, using the Analytic Hierarchy Process (AHP) to determine indicator weights and ArcGIS for spatial visualization. Multi-source geospatial data, including land use, NDVI, DEM, and socio-economic datasets, were integrated. The results revealed the following: (1) Overall moderate EECC levels with stronger terrestrial capacity contrast with weaker marine capacity—high-carrying zones being limited to nearshore areas; (2) The overall EDS level was favorable, where southern section significantly outperformed northern zones, forming concentrated high-suitability clusters encircling lower-suitability areas; (3) Marine EDS slightly exceeds terrestrial suitability, with optimal coastal zones transitioning landward toward progressively higher suitability. This research provided a replicable methodology for ecotourism suitability assessment in coastal protected areas and supported sustainable spatial planning in land–sea integrated national parks. Full article

The ecological restoration of degraded alpine steppe is a critical component of ecological conservation efforts on the Qinghai–Tibetan Plateau. In this study, we investigated the effects of fertilization, reseeding, and combined fertilization with reseeding restoration measures on the vegetation community, soil properties and microbial community diversity in degraded alpine steppe through field vegetation surveys, and soil microbial high-throughput sequencing at an experimental site of fertilized and reseeded grassland restoration located in the Yellow River Source area. The results demonstrated the following: (1) both reseeding and combined fertilization with reseeding restoration measures significantly affected grassland vegetation community structure and diversity; (2) fertilization and combined fertilization with reseeding restoration measures significantly affected soil pH and total phosphorus (TP) content; (3) while fertilization and combined fertilization with reseeding restoration measures markedly altered microbial community structure, reseeding alone significantly affected microbial diversity. Co-occurrence network analysis revealed that soil microbial communities were significantly influenced by fertilization restoration measures; redundancy analysis (RDA) showed that microbial communities under fertilization and combined fertilization with reseeding restoration measures were primarily governed by soil TP, whereas those in control and reseeding plots were strongly associated with soil pH and organic carbon (SOC). This study explored effective restoration measures suitable for degenerating alpine steppe in the Yellow River Source area, aiming to provide a scientific basis and technical support for the ecological protection and restoration of the Three-River Headwaters. Full article

Understanding the tradeoff and synergy among ecosystem services (ESs) and their influencing factors is a prerequisite for simultaneously managing multiple ESs and holds significant importance for achieving harmonious regional development between humans and nature. Existing research predominantly focuses on the overall characteristics of tradeoff and synergy, while studies on spatially differentiated tradeoff and synergy characteristics remain limited. In addition, their driving mechanisms are not yet fully understood, especially in large-scale river basins. This study, taking the Yellow River Basin (YRB) from 2000 to 2023 as the study area, employed multi-source data and multiple models to quantify three ESs, including soil erosion negative service (indirectly reflecting the soil conservation service function), carbon sequestration, and water yield. Combining Pearson correlation analysis, a geographically weighted regression model, and optimal parameter geographical detection, we identified the spatiotemporal interaction relationships and their dominant drivers. The results indicated that soil erosion negative services decreased by 24.89%, while carbon sequestration and water yield increased by 53.30% and 38.47%, respectively. The most significant improvements in the three ESs were observed in the midstream of the YRB. Spatially, soil erosion negative service decreased from west to east. Carbon sequestration exhibited a spatial pattern of higher values in the south and east and lower values in the north and west. Water yield decreased from south to north. Tradeoff relationships existed between soil erosion negative service and carbon sequestration and between soil erosion negative service and water yield. A synergistic relationship existed between carbon sequestration and water yield. Over time, the proportion of areas showing synergy among these three ESs decreased. However, synergistic areas remained more common than tradeoff areas. This was especially evident in the relationship between carbon sequestration and water yield, where synergy consistently accounted for over 78% of the YRB. Rainfall, soil properties, and fractional vegetation cover were identified as important drivers of the tradeoff/synergy between soil erosion negative service and carbon sequestration. Rainfall, temperature, fractional vegetation cover, and elevation were significant drivers of the interactions between carbon sequestration and water yield. Population density, fractional vegetation cover, GDP density, and rainfall were the main influencing factors for the tradeoff/synergy between soil erosion negative service and water yield. Our general methodology and results provide valuable decision-making references for policymakers, highlighting the necessity of considering the spatiotemporal heterogeneity in ESs tradeoff characteristics and their underlying driving factors. Full article

Urban spatial justice is a critical issue in the context of rapid urbanization. Improving public well-being depends on the efficient use of park green space (PGS) resources. This study evaluates the spatial distribution equity and social equity of PGS in Jinan City, Shandong Province, China, with the aim of optimizing their spatial layout, mitigating poor accessibility due to uneven spatial distribution, and improving the quality of life for all inhabitants. Firstly, based on Sustainable Development Goal 11 (SDG11), we constructed an urban sustainable development index system to quantify residents’ demand levels. The supply level was measured through three dimensions: quantity, quality, and accessibility of PGS utilizing multi-source geospatial data. A coupling coordination degree model (CCDM) was employed to analyze the supply-demand equilibrium. Secondly, Lorenz curves and Gini coefficients were utilized to evaluate the equity of PGS resource distribution to disadvantaged populations. Finally, a k-means clustering algorithm found the best sites for additional parks in low-accessibility regions. The results show that southern areas—that is; those south of the Yellow River—showed greater supply-demand equilibrium than northern ones. With a Gini index for PGS services aimed at vulnerable populations of 0.35, the citywide social level distribution appeared to be relatively balanced. This paper suggests an evaluation technique to support fair resource allocation, establishing a dual-perspective evaluation framework (spatial and social equality) and giving a scientific basis for PGS planning in Jinan. Full article