Promoting the coordinated development of different elderly care models is an effective way to optimize the allocation of elderly care service resources in our country. Based on panel data from 2018 to 2022, this study empirically analyzes spatiotemporal coupling coordination and influencing factors of home community elderly care and institutional elderly care in China using a coupling coordination model, a geographic detector, and other methods. The results indicate that (1) The coupling coordination degree and relative development degree between home community elderly care and institutional elderly care are generally on the rise. The coupling coordination degree has shown a continuous improvement trend over time. The relative development degree of home community elderly care is gradually becoming clear with the trend of “synchronous development>advanced development>lagging development”. (2) The number of provinces entering the coordination stage (III and IV) continues to increase and shows an evolutionary pattern of gradually spreading from the central and eastern regions to the western and northeastern regions in space. The phenomenon of stage transition in relative development is more pronounced, and the western region has significantly more provinces in transition than the central and eastern regions. (3) The coupling coordination degree has a positive spatial correlation and a fluctuating upward trend. The correlation strength shows a spatial pattern of “western>eastern>central>northeast”, with mostly HH-type and LL-type clustering. (4) Organizational strength, elderly care demand, and technological level are the main influencing factors of the coupling coordination degree. This study’s findings can provide a theoretical basis and policy recommendations for addressing structural contradictions in China’s elderly care service supply and for innovating the development of the elderly care policy system.

This study employs the theory of the “six elements” of tourism and utilizes spatial analysis methods, including nearest neighbor index, kernel density analysis, bivariate spatial autocorrelation, and Ripley’s K-function, to examine the spatial distribution and correlation characteristics of point of interest data related to tourism elements in the urban agglomeration on the northern slope of the Tianshan Mountains in Xinjiang of China based on data collected in April 2024. In addition, we explore the influencing factors using a geographical detector. The results show the following. (1) The spatial distribution characteristics of each tourism element exhibit significant concentration, with the degree of spatial agglomeration ranking from high to low as follows: “food”>“shopping”>“accommodation”>“transportation”>“entertainment”>“tourism”. (2) Each tourism element demonstrates weak spatial continuity, resulting in a distribution pattern characterized by “one core, one axis, and multiple centers”. At the county level, the spatial correlation among tourism elements is generally weak; however, a strong correlation exists between the “transportation” element and other elements, whereas the “tourism” element exhibits weak correlations, indicating a need for optimization in the spatial distribution of tourism elements. (3) The characteristic value of the overall spatial agglomeration scale of the “six elements” of tourism is 33.83 km. Among the different elements, the “tourism” factor shows the largest spatial agglomeration scale eigenvalue (42.95 km), whereas the “accommodation” factor has the smallest (18.48 km). (4) The influence of the interaction between each factor on the spatial pattern of tourism elements is significantly greater than that of any single factor. This research highlights the effects of multi-dimensional factors, including economic development level, infrastructure, and population on the spatial pattern of tourism elements, with GDP, night light index, number of A-level scenic spots, population density, and the proportion of the tertiary industry having the most significant effects.

In the overall national security concept in the new era, historical blocks are facing dual challenges of disturbances and resilience building. Taking the historical block of Kashi Old City as the research object, this studybuilds a pressure-state-response model comprising six elements: Extreme disaster pressure, climate environment pressure, alley composition capacity, alley component density, infrastructure response, and public service response. It selects 44 key factors closely related to resilience to natural disturbances and uses the entropy weight method and the analytic hierarchy process to establish a multidimensional resilience evaluation system for historical blocks. The evaluation results show that (1) The comprehensive resilience index of the historical block of Kashi Old City is 1.84 (Level II), and the overall coping ability is weak. The resilience of the state layer (38.83%) is significantly higher than that of the response layer (27.45%), indicating its strong self-regulating ability but weak postdisaster management. (2) The key restrictive factors are the flood inundation radius, historical street and alley greening rate, and average summer solar radiation intensity, highlighting the synergistic risks between high-density built environments and climate sensitivity. (3) The wisdom of traditional construction is not linked to modern disaster prevention needs, leading to a contradiction between protection and safety. The results reveal a quantitative framework for integrated multi-hazard defense and living conservation of historic districts in arid zones, thereby promoting the synergistic development of cultural heritage conservation and ecological security.

Tourism is an important industry in Xinjiang, and sports tourism plays an important role in promoting tourism strategies to prosper Xinjiang of China. Identifying the characteristics of spatial distribution and influencing factors of sports tourism resources can provide a scientific basis for the sustainable development of the sports tourism industry in Xinjiang. Adopting the sports tourism resources in Xinjiang in 2022 as the research object, this study uses exploratory spatial data analysis and geographical detectors to quantitatively explore their spatial distribution characteristics and influencing factors. The results indicate that: (1) The spatial distribution of sports tourism resources across Xinjiang in 2022 shows a significant imbalance, with a highly aggregated distribution, mainly concentrated in Urumqi, Changji Hui Autonomous Prefecture, and Ili Kazakh Autonomous Prefecture; on the whole, it is distributed more across the north and less across the south, forming a three-core spatial distribution pattern; in addition, the spatial dependence is obvious, with large differences being spatially correlated and with an uneven distribution of coldspot and hotspot areas. (2) The spatial distribution of sports tourism resources in Xinjiang is affected by such multi-dimensional factors as geography, traffic, and resources, among which, the average annual precipitation, distance from transportation hubs, average annual temperature, and elevation are the main influencing factors, while the road network density and amount of population have relatively minimal influence; this type of interaction is mainly dominated by dual-factor enhancement, indicating that the spatial distribution of sports tourism resources in Xinjiang is the result of the joint action of multiple factors. From this, scientific and reasonable suggestions are put forward for the sustainable development of the sports tourism industry in Xinjiang.

While the synergistic development of rural public services and rural tourism is critical for advancing rural revitalization, academic research focusing on coupling coordinated development between these two domains remains notably scarce. This study analyzes coupling coordination between rural public services and rural tourism and its impact on rural revitalization, This study uses methods including the coupling coordination degree model, the gravity center and standard deviation ellipse model, and spatial econometric models to quantitatively measure the spatiotemporal characteristics of the coupling coordination degree between the two in western China from 2010 to 2023, as well as their impacts and spatial spillover effects on rural revitalization. The findings reveal that the coupling coordination between rural public services and rural tourism in western China has increased year by year, with the overall level shifting from extreme disorder to intermediate coordination, and presenting a spatial differentiation pattern of high coupling coordination in the south and northwest, and low in the northeast. The gravity center of the coupling coordination degree exhibited a southwestward migration trend, while the standard deviation ellipse consistently maintained a northwest-southeast orientation, demonstrating a trend of first clustering and then dispersing. Furthermore, the degree of coupling coordination has a significant positive impact on rural revitalization and exhibits spatial spillover effects. The research findings can provide a theoretical basis and policy recommendations for the coordinated development of the two aspects and the region’s overall rural revitalization.

Tourism is a strategic pillar industry of the national economy, playing a role in cultural prosperity, national unity and stabilizing the border. Border ethnic areas in western China are rich in cultural and tourism resources, and promoting the high-quality development of cultural and tourism integration is an important hand in promoting the interaction, communication and integration of various ethnic groups and casting a firm sense of Chinese national community. Taking the border ethnic areas as the research object, based on the multi-indicator panel data from 2011 to 2020, we measure the level of high-quality development of culture and tourism, analyze the spatiotemporal evolution of the coordination degree, and identify the driving factors. The study found that: (1) The level of high-quality development of culture and tourism in the border ethnic areas is generally on the rise, the impact of the new crown epidemic on tourism is obvious in 2020, and the level of high-quality development of culture is higher than the level of high-quality development of tourism due to the influence of historical and cultural precipitation and cultural exchanges. (2) The degree of coordination of high-quality development of cultural and tourism integration in all provinces and regions is rising in fluctuation, and the level of coordination is gradually optimized. The coordination level of high-quality development of cultural and tourism integration is higher in Guangxi and Yunnan, forming the “Matthew effect”. (3) The investment level, policy support, market supply and transportation conditions are the important driving force for the high-quality development of cultural and tourism integration in the border ethnic areas, among which the investment level shows the strongest utility. The results of the study provide theoretical basis and data support for the high-quality development of culture and tourism integration in border ethnic areas, which can help strengthen the construction of cultural tourism, realize the transformation and upgrading of tourism, and enhance the vitality and influence of culture.

Climatic dry-wet conditions are important indicators of climate characteristics, whereas soil dry-wet conditions are complex and multidimensional hydroclimatic concepts. There are significant differences and certain consistencies between these conditions. Under the background of global warming, the evolution trends and differences of these conditions must be further studied. Thus, this paper analyzed the characteristics and differences of climate dry-wet and soil moisture conditions in China and clarified their similarities and differences. Therefore, the overall climate dry-wet status and regional fluctuation were studied using the humidity index, and the soil dry-wet trends were analyzed in the same period. The results showed little change in the boundary line of different climates in China over the past 60 years. However, compared with the climate state period from 1961 to 1990, there was a vast climate drying zone from west to east in the north of China and its humidity index had a slightly decreasing trend, but the variation did not necessitate changing the climate classification. The monthly variations of climate dry-wet and soil dry-wet conditions were different in each climate zone in China, and the consistencies of humid and semihumid zones were better than those of semiarid and arid zones. The monthly variations of PET and precipitation differences in each climatic region in China were obviously different. For arid and semiarid regions, March-September and March-June were dry periods, respectively, and drought was more likely to occur in these periods. The semihumid climate area entered the water surplus stage from July to August, whereas the humid climate area, except for a few months, was basically in the water surplus state throughout the year. There were obvious differences between climate dry-wet changes and perennial soil moisture changes in China’s land regions. The annual humidity index in different climate regions showed a slightly increasing trend, but most of the soil moisture showed a drying trend, especially the shallow soil in the plough layer, which showed a potentially increasing agricultural and pastoral drought risk in different climate regions of China. The results of this study can help us fully understand the relationship between climate dry-wet and soil dry-wet conditions and promote further studies on their relationships. Moreover, this study can strengthen the awareness of drought risk prevention and control and improve agricultural and pastoral drought resistance measures.

The three subsystems of ecology, tourism, and culture form an interactive complex system, and their coordinated development is essential for promoting regional sustainable development. Using panel data from 31 Chinese provinces from 2011 to 2022, this study constructs a comprehensive development evaluation index system for the “ecology-tourism-culture” system. The comprehensive evaluation function model, coordination degree model, and fuzzy-set qualitative comparative analysis method are employed to examine the spatiotemporal differentiation and influence paths of coordinated development within the system. The results indicate the following: (1) The comprehensive development levels of the three subsystems vary, and the comparison order of index mean is natural ecology>ecology>social ecology>culture>tourism. Throughout this period, the ecological subsystem continues to demonstrate carrying capacity. (2) The overall coupling coordination degree of the “ecology-tourism-culture” system exhibits a cyclic alternating trend of “decline-increase”, rising from 0.507 in 2011 to 0.526 in 2022 and fluctuating between near imbalance and barely coordinated levels. The comparative ranking of regional coupling coordination degree is eastern>central>northeast>western, reflecting a distribution characterized by “high in the southeast and low in the northwest”. (3) The types of highly coordinated development include diversified development, government-led industry, and economy-market-technology driven paths, whereas non-highly coordinated development is constrained by government and technology limitations.

This study examines 474 national nature reserves in China from 1956 to 2023, utilizing kernel density estimation to analyze their spatiotemporal distribution patterns. A social network analysis model is then employed to measure the attributes of these reserves and to propose integrated protection strategies. The findings reveal the following. (1) The evolution of China’s national nature reserves can be categorized into four distinct stages: Preliminary exploration, vigorous development, slow development, and consolidation and improvement. This development has resulted in a spatial pattern characterized by large and scattered reserves in the west, and small and clustered reserves in the east. (2) Topological analysis reveals that the nodes within the national nature reserve network exhibit strong cohesion, small-world characteristics, and a prominent “core-periphery” effect. (3) The network’s spatial pattern demonstrates significant heterogeneity among protection clusters, forming a “triangular” framework for reserve aggregation, with key vertices located in the middle and lower reaches of the Yangtze River, the Northeast Plain, the Changbai Mountain area, and the Qinghai-Xizang Plateau. Based on the natural endowments and geographic conditions of these reserve clusters, we propose corresponding integrated protection strategies from the perspective of the association network, aimed at providing guidance for the integration and optimization of nature reserves.

With the acceleration of global urbanization, the severe PM_2.5 pollution in arid zone cities, owing to their unique geographical and climatic conditions, exhibits strong non-stationarity and complex spatiotemporal characteristics, making it difficult for traditional prediction models to effectively capture its dynamic patterns. To address this challenge, this study proposes a hybrid prediction framework of an “adaptive noise complete ensemble empirical mode decomposition-Ivy optimization algorithm-Kolmogorov Arnold network-bidirectional long short-term memory neural network” (CEEMDAN-IVY-KAN-BiLSTM), aiming to enhance the prediction accuracy of PM_2.5 concentrations. This framework jointly extracts multi-scale features through noise reduction decomposition as well as parameter optimization and integrates the strong nonlinear fitting and bidirectional time series modeling capabilities of the KAN-BiLSTM model, effectively improving the prediction performance. The results reveal that the PM_2.5 concentration in Urumqi City from 2021 to 2024 shows significant seasonal fluctuations, with an average of 41.97 μg·m^-3 in winter due to coal heating and the influence of the inversion layer and drops to 14.04 μg·m^-3 in summer due to enhanced atmospheric convection. Moreover, it shows an overall decreasing trend annually. Moreover, the importance ranking of the data indicates that PM_2.5 is significantly positively correlated with air quality index, PM₁₀, CO, and NO₂, and negatively correlated with temperature and dew point temperature, suggesting that coal emissions, vehicle exhaust, and meteorological diffusion conditions are the main influencing factors. Moreover, the model effectively separates the high-frequency fluctuations (such as sandstorm events) and low-frequency trends (seasonal changes) in the PM_2.5 sequence, reducing the impact of data non-stationarity. Finally, the experiments were based on daily air quality data in Urumqi City from 2021 to 2024, results of which demonstrate that this model achieves the coefficient of determination, mean absolute error, and root mean square error values of 0.991, 1.391, and 1.881, respectively, significantly outperforming conventional machine learning and common deep learning models. This verifies the applicability of the “decomposition-optimization-integration” deep learning framework in the prediction of arid zone cities.

Ski resorts play a significant role in ice and snow tourism. Focusing on ski resorts in China, this paper systematically explores their spatial distribution patterns and underlying causes using various spatial analysis techniques. The results indicate the following: (1) Ski resorts in China exhibit a condensed distribution trend, following a “northeast-southwest” axis roughly along the “Beijing-Zhengzhou-Chongqing” line. (2) The spatial structure of national ski resorts is characterized by “one pole, one core area, one belt” with the Beijing-Tianjin-Hebei region as the development pole, the Yangtze River Delta as the development core, and the three northeastern provinces forming a high-density development belt. (3) The hotspots of national ski resorts are concentrated in Northeast China, with Liaoning Province, Jilin Province, Heilongjiang Province, Beijing City, and Hebei Province being the most active in ski resort development. (4) The human factors influencing the spatial distribution of ski resorts, in descending order of impact, are industrial support and guidance, living standards, market cultivation and development, tourism economic income effect, transportation capacity, and hardware service support. Naturally, ski resorts tend to be located in low mountains ranging from 500 m to 800 m above sea level, within a 10 km buffer zone of third-class rivers, and in the temperate monsoon climate zone.

Soil salinization is a major factor in arid and semi-arid regions, adversely affecting agricultural production and the ecological environment. Accurately capturing the spatiotemporal distribution of soil salinization has become a key focus in current research across the fields of ecology, geography, and agriculture. In this study, Sentinel-2A imagery from April and July, along with corresponding in-situ measurements of the salinity of surface soil, were utilized to construct soil salinity inversion models for the Ebinur Lake region. Five machine learning algorithms [random forest (RF), support vector regression, decision tree regression, adaptive boosting (Adaboost), and gradient boosting regression tree] and two deep learning methods(deep belief network and fully convolutional network] were employed for this purpose. Variables were selected using the Boruta algorithm to enhance the performance of the model. The results indicate that: (1) In April, the soil salinity exhibited a strong positive correlation with various spectral bands, whereas the overall correlation strength decreased in July. Among multispectral indices, the intensity indices (Int₁, Int₂), salinity indices (S₃, S₅, S₆, SI, SI₁, SI₂, SI₃), and the ratio index showed strong positive correlations with the soil salinity, whereas the normalized difference index displayed a strong negative correlation. (2) The RF model achieved the highest predictive accuracy in both time periods, with an average R² and RMSE of 0.72 and 0.13 in April and 0.66, and 0.15 in July, respectively. Therefore, the RF model was identified as the optimal model in this study. Furthermore, in terms of temporal selection, soil salinity inversion in April yielded higher accuracy compared to July, indicating that April is more favorable for soil salinity monitoring in arid regions.

Using daily rainfall data from 45 national meteorological observation stations in southern Xinjiang of China from 1961 to 2022, we analyzed the spatiotemporal distribution and variability of rainfall, identified extreme rainfall thresholds, and examined extreme rainfall characteristics. The results show that (1) Over the past 62 years, the region with the highest and most rapidly increasing annual average rainfall in southern Xinjiang has been located in the middle mountain belt at an altitude of 1500-2500 m, with a growth rate of 5.4 mm·(10a)^-1. This increase is mainly reflected in the greater number of rainfall days, particularly large-scale rainfall days, while the increase in heavy-rainstorm-level rainfall and above is especially pronounced. (2) Based on a comparative analysis using the percentile method, the 99^th percentile was identified as the threshold for extreme rainfall in southern Xinjiang, corresponding to 14.1-35.4 mm. Thresholds in the western and mountain-adjacent regions are higher than those in the eastern basin-desert areas, and the extreme rainfall threshold has increased at a rate of 0.7 mm·(10a)^-1. Stations with the most rapid increases are primarily located in the mountainous areas of Kashgar, western Hotan, and northern Bayingol Mongolian Autonomous Prefecture. (3) Over the past 62 years, the number of extreme rainfall events in southern Xinjiang has generally ranged from 10-20 times, while in the Tianshan Mountains, events can persist for more than 20 times. Extreme rainfall events have increased in frequency at a rate of 0.9 events per decade.

Under the background of “four waters and four determinations”, scientific and quantitative assessment of water conservation capacity is the basis for ensuring high-quality social and economic development and effective protection of the ecological environment. As an important part of the “double evaluation”, the evaluation of the importance of ecological protection plays a guiding role in the evaluation of agricultural production and urban construction. Based on the InVEST water yield module, the water conservation volume was obtained by using the terrain index, soil saturation water conductivity and flow velocity coefficient to obtain the water conservation volume, and the temporal and spatial evolution of water conservation in Lanzhou City of Gansu Province, China from 2000 to 2020 was quantitatively evaluated, and the impact of land use type change on it was discussed, and the importance level of water conservation function was divided. The results showed that: (1) From 2000 to 2020, except for the decrease of farmland area, the area of other land use types increased, and the increase of grassland was the most significant. (2) The spatial distribution of water conservation in Lanzhou City was “high-low distribution”, and the average unit water conservation was 15.42 mm, and the total water conservation volume was 2.03×10⁸ m³. From 2000 to 2020, the average unit water conservation and total amount in Lanzhou increased, and the increase rate gradually increased. (3) The total water conservation of different land use types in Lanzhou is as follows: grassland>farmland>woodland>impervious surface>bare land>shrubs. Among them, the average unit water conservation capacity of forest land was the largest, while the total water conservation of grassland was the largest. (4) From 2000 to 2020, the area of the generally important and relatively important areas of water conservation function in Lanzhou decreased, and the area of moderately important, highly important and extremely important areas increased. The evaluation and importance classification of water conservation functions can provide scientific reference and guidance for consolidating the existing achievements of returning farmland to forest and grassland, promoting the construction of ecological civilization, and promoting regional economic development in China’s arid areas.

The interaction between tourism and urbanization has become increasingly significant, and the coupling coordination of tourism and urbanization is crucial for the promotion of the high-quality development of regional tourism economies. Using the coupling mechanism of tourism efficiency and urbanization with the Super-SBM model, the entropy method, the coupling coordination degree model, and the obstacle degree model, this study explores the spatiotemporal evolution characteristics and the obstacle factors of the coupling of tourism efficiency and urbanization in a core section of the Belt and Road (six provinces, including Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, and Inner Mongolia) from 2000 to 2022. The results show that: (1) The average tourism efficiency of the six provinces is 0.73, which is low; the overall level of urbanization is growing steadily, with obvious inter-provincial differences. (2) The coupling coordination degree of tourism efficiency and urbanization in the six provinces has evolved from a near imbalance to primary coordination, with a spatial pattern of distribution that is higher in the southeast and lower in the northwest, and with a center of gravity showing an offset southeast-northeast-southwest pattern, with the degree of agglomeration to the southeast region gradually increasing. (3) The key obstacle factors constraining the degree of coupling coordination of tourism efficiency and urbanization are total tourism revenue, total number of tourists, total postal and telecommunication businesses, number of students in general higher education institutions, and the amount of employees in the tourism industry. The results of the study provide a scientific basis for the high-quality synergistic development of regional tourism and urbanization.

“Xinjiang Gifts” is a comprehensive tourism brand established by the government through selecting products from various enterprises in accordance with relevant documents, integrating both commodity attributes and cultural/humanistic elements. This study uses 1563 selected commodities from “Xinjiang Gifts” (2013—2022) as research samples and applies spatial analysis techniques and the geodetector method to examine the structural patterns, spatiotemporal differentiation, and influencing mechanisms of “Xinjiang Gifts” at the county level in Xinjiang. The results show that (1) The category structure of “Xinjiang Gifts” is diverse, with notable quantitative differences—traditional handicrafts and agricultural, forestry, animal husbandry, and fishery products dominate in number. The structure of each category remains stable, with the largest increase observed in the food and culinary product category and the lowest increase in traditional handicrafts. (2) “Xinjiang Gifts” generally exhibit a spatial distribution pattern of “more in the north and fewer in the south, stronger in the west and weaker in the east”. The spatial agglomeration first increased from 2013 to 2019 and then weakened after 2019, indicating an overall weakening trend. The kernel density distribution reveals a core-edge structure characterized which decrease outward from the central cities of each prefecture-level region, with notable spatial heterogeneity among commodity types. (3) The key drivers of the spatiotemporal differentiation of “Xinjiang Gifts” are tourism revenue, the number of industrial enterprises above designated size, the total number of visitors, and the total retail sales of consumer goods. These factors reflect a transition from a market demand-driven to a economic society­driven pattern, with the influence dimensions ranked as market demand>economic society>resource endowment. (4) The influence mechanism of “Xinjiang Gifts” is constructed such that resource endowment serves as the internal foundation, the economic society acts as the institutional guarantee, and market demand functions as the external driving force.

The project titled “Scientific Investigation of Water Resources Development Potential and Utilization Pathways on the northern Slope of the Kunlun Mountains” was initiated in October 2021 as part of the initial set of projects for the Third Xinjiang Scientific Expedition. This study integrates multi-source remote sensing data and field research conducted from 2022 to 2023 to examine hydrological changes, water resources dynamics, and water resource utilization patterns on the northern slope of the Kunlun Mountains. The findings reveal the following: (1) A temperature increase of 0.14 ℃·(10a)⁻¹ and precipitation increase of 6.53 mm·(10a)⁻¹ from 1990 to 2020 was observed on the northern slope of the Kunlun Mountains. (2) Glacier variations have remained relatively stable, with a slight expansion observed in snow cover area and depth. (3) Permanent water bodies have experienced a significant growth rate of 79.89%, while seasonal water bodies have expanded by an impressive margin of 144.49%. (4) Ayakkum Lake and Akikkule Lake, two major lakes within the Kumukuli Basin, witnessed increases in their water areas by approximately 68.91% and 58.22%, respectively, and several rivers within this basin exhibit potential for further development regarding water resources utilization. (5) Terrestrial water storage on the northern slope of the Kunlun Mountains generally exhibits an increasing trend, particularly more pronounced from west to east. (6) Average annual runoff of Hotan River, Keriya River, and Qarqan River, the main rivers on the northern slope of the Kunlun Mountains, increased by 20.24%, 27.85%, and 45.17%, respectively, during the period of 2010—2023 when compared with the period of 1957—2023. (7) Based on simulations considering different climate change scenarios, it is predicted that major river runoff will continue to increase throughout the middle-to-later stages of the 21^st century, alongside regional augmentation in available water resources. The conditions of water resources on the northern slope of the Kunlun Mountains can provide favorable water resources for the green development of the region.

The systematic analysis of the factors influencing urban ecological resilience and improvement in its levels are essential for achieving sustainable urban development and fostering “resilient cities”. Based on panel data from 281 prefecture-level cities of China collected between 2005 and 2021, this study constructed evaluation indexes across three dimensions: resistance, adaptability, and resilience. The spatial and temporal evolution of urban ecological resilience were characterized, and spatial and temporal geographically weighted regression models were applied. In addition, a global trend analysis was conducted to explore the spatial and temporal heterogeneity of influencing factors. The results showed the following. (1) From 2005 to 2021, the ecological resilience level of Chinese cities increased from 0.0207 to 0.0248, with an average annual growth rate of 1.140%. Over this period, the center of gravity for ecological resilience shifted along a northeast-southwest direction. The difference in ecological resilience levels initially expanded but then narrowed. (2) Economic development, industrial structure, topographical factors, environmental regulations, and human capital demonstrated positive effects on urban ecological resilience. However, the influence of these factors exhibited obvious spatial and temporal heterogeneity, with their effects varying significantly in terms of magnitude and direction across different regions. (3) The impact of influencing factors on urban ecological resilience exhibited a greater variation along the east-west direction compared to the north-south direction. The ecological resilience was observed to be most sensitive to changes in industrial structure along the east-west direction, while environmental regulation had the greatest sensitivity along the north-south direction.

The typical meteorological year (TMY) is crucial for assessing solar energy resources, significantly impacting the scientific evaluation of regional solar resource assessments and the optimal design of photovoltaic power generation systems. These systems directly influence the technical and economic performance of solar energy utilization. With ongoing climate warming, key indicators of the climate system have shown rapid changes. Over the past 60 years, global surface solar radiation initially decreased and then increased. However, since the 1980s, approximately 25% of observation stations have recorded a continuous decline, highlighting significant temporal and spatial variations in surface solar radiation. Xinjiang, China, a region sensitive to global climate changes, has experienced significant shifts in temperature, precipitation, and other meteorological elements. This study analyzes global horizontal irradiations (GHI) data collected from eight stations in Xinjiang from 1961 to 2022, examining temporal and spatial variations. Additionally, using wind speed, temperature, humidity, and dew point temperature data, we employed the Sandia method to select the TMY for solar energy resource assessment. We compared the differences in GHI TMY selected with the Sandia method every 30 years (four standard climatological normals of 1961—1990, 1971—2000, 1981—2010 and 1991—2020). The findings indicate that while GHI in northern Xinjiang initially decreased and then increased, it continued to decline in southern and eastern Xinjiang from 1961 to 2022. Post-1990s, the rate of decline slowed. Seasonally, GHI reduction rates in autumn and winter were notably higher than that in spring and summer. The GHI values of TMY calculated with the Sandia method were close to the annual average, with a relative error within ±3%. As meteorological elements changed, the absolute error between TMY with Sandia and the annual average increased. Furthermore, monthly GHI exhibited considerable volatility, with fluctuations notably larger between 1981—2000 and 1991—2020 compared to earlier periods. In these four periods, the variability in typical months was less in northern Xinjiang than that in the south and east due to smaller interannual GHI variations. The highest monthly GHI values in TMY typically occurred from June to July, while the values from January to March were generally higher than those from October to December.

It is very important to reduce regional social vulnerability to natural disasters and integrated risk governance. At the county and district unit scale, a social vulnerability assessment index system was constructed for three disaster-bearing bodies that would be suitable for Gansu Province: Population, economy and agriculture. The social vulnerability of natural disasters in Gansu Province was evaluated, including exposure, sensitivity, and adaptability. Then, based on the paradigm of natural geographic regionalization, a comprehensive social vulnerability regionalization was developed. The results show the following: (1) The comprehensive social vulnerability index in Gansu Province is generally high in the east, low in the west, high in the south, and low in the north. High-vulnerability areas are mainly concentrated in the eastern, central, and southern regions of Gansu, and they cluster in densely populated disaster-prone areas, such as cities and nearby counties. (2) Comprehensive regionalization includes two levels: The first level is divided into four leading natural disaster types, including sandstorm-leading disaster areas in the western section of the Hexi Corridor, the Lanzhou drought-leading disaster area, the southern Gansu rainstorm flood landslide/debris flow-leading disaster area, the central-eastern Hexi Corridor, and east, central, and southern Gansu multihazard disaster areas. Secondary-level zones include 14 comprehensive vulnerability level zones with different structures. The regionalization scheme systematiclly expresses macrospatial differentiation in social vulnerability structures under regionally dominant natural disaster types that can serve diverse regional differences and help reduce social vulnerability to natural disasters.

Civil aviation transport is the material subject of the passage for inbound passengers to China and is essential for realizing the value of tourism products. Collecting economic data from 31 Chinese provinces, cities, and autonomous regions from 2011 to 2022 and based on the degree of development of the inbound tourism economic with zonal measurement method, this study explores the heterogeneity spillover of air transportation to inbound tourism. By expanding single time series data to temporal and spatial panel data and establishing a spatial econometric model to simulate empirical results, the study concludes that: (1) China’s inbound tourism industry generally presents a trend of aggregation and cooperation. (2) Spatial differences exist in the cross-regional spillovers of inbound tourism caused by civil aviation transport. In regions with developed inbound tourism, the spillover is positive, while in areas with underdeveloped inbound tourism, it is negative. (3) Different regions have varying spatial agglomeration characteristics of inbound tourism. In regions with developed inbound tourism, a pronounced competitive agglomeration effect is present. In underdeveloped areas of inbound tourism, no-agglomeration characteristics are evident and tourism production factors have no spatial correlation. This research provides a theoretical basis for the rational allocation of civil aviation resources, promoting the regional integration of inbound tourism in China and contributing to its high-quality development.

Evaluating rural development from a resilience perspective is significant for breaking the urban-rural dual structure and promoting comprehensive rural revitalization. This article takes 86 counties in Gansu Province as the research object and constructs a rural resilience evaluation index system based on three dimensions: “resilience, adaptability, and reconstruction capability”. Using spatial autocorrelation analysis and geographic detector models, it reveals the spatiotemporal evolution of rural resilience and its driving mechanisms in counties of Gansu Province from 2010 to 2022. The results indicated that (1) The resilience level of rural areas in Gansu Province has significantly improved, with obvious spatial differentiation characteristics. The resilience of rural areas in central and eastern Gansu is relatively high, while some counties in Hexi, Gannan, and Linxia have lower resilience. The number of high-resilience counties continues to increase, while the number of low-resilience counties continues to decrease. (2) There is a spatial positive correlation in rural resilience, and the correlation is gradually weakening. The degree of spatial agglomeration is declining, with high-agglomeration areas shrinking toward the central Gansu region and low-agglomeration areas concentrated in counties such as Gannan and Linxia. (3) The level of rural social services, economic development, and agricultural production has a significant impact on rural resilience. The explanatory power of rural industrial structure for rural resilience is steadily increasing, and rural resilience is driven by economic development, resource optimization, industrial transformation, and service guarantee mechanisms. This study’s results provide scientific reference for the implementation of rural resilience development in Gansu Province.

Based on six carbon sources in agricultural production, namely fertilizers, pesticides, agricultural films, diesel oil, plowing, and agricultural irrigation, this study applied the carbon emission coefficient method proposed by the United Nations Intergovernmental Panel on Climate Change to measure and analyze the spatiotemporal variation in agricultural carbon emissions at provincial and municipal scales in the Yellow River Basin of China from 2005 to 2020. The spatial heterogeneity of the influencing factors was assessed using a geographically weighted regression model. The conclusions are as follows: (1) From 2005 to 2020, agricultural carbon emissions in the Yellow River Basin initially increased before declining, following an overall upward trend. Emissions rose from 4431.95×10⁴ t in 2005 to 4915.87×10⁴ t in 2020. Among the carbon sources, fertilizers and plowing were the primary contributors, accounting for more than 65% of total agricultural carbon emissions. Pesticide-related carbon emissions consistently remained the lowest. (2) In 2005, Shandong Province was the leading contributor to agricultural carbon emissions in the Yellow River Basin, with emissions of 1241.68×10⁴ t. However, from 2010 to 2020, Henan Province became the largest emitter, with annual emissions ranging from 1360×10⁴ t to 1470×10⁴ t. Qinghai Province consistently recorded the lowest agricultural carbon emissions. In 2020, agricultural carbon emissions at the municipal scale exhibited a stepped decline from east to west in the Yellow River Basin. (3) The positive effect of agricultural production efficiency on agricultural carbon emissions was stronger in the southeast and northwest and lower in the northeast of the Yellow River Basin. The negative impact of agricultural structure was most pronounced in Shanxi Province. The highest positive impact of agricultural economic development was observed at the borders of Shaanxi Province, Shanxi Province, and Henan Province. The positive effect of the agricultural labor force was higher in the southeast and northwest and lower in the southwest.

Rural revitalization is a key strategic measure for China to achieve the comprehensive construction of a modern socialist country. Drawing on the connotation of the rural revitalization strategy, this paper constructs an evaluation index system to measure the level of rural revitalization development. It uses the entropy method to assess the rural revitalization development level of 85 counties (districts) in Gansu Province, China, from 2013 to 2022 and utilizes the Dagum coefficient and kernel density estimation to analyze regional differences in rural revitalization. The results indicate that: (1) The overall level of rural revitalization and development in Gansu Province is on the rise, with the most significant growth being observed in industrial prosperity and ecological livability. (2) The level of rural revitalization and development among counties in Gansu Province exhibits a pattern of spatial distribution characterized by being high in the northwest and low in the southeast. High-level areas are concentrated in the Hexi region, and low-level areas are primarily located in the Hedong region. (3) The overall Dagum coefficient for the level of rural revitalization demonstrates a fluctuating trend downward, with interregional differences marking the primary source of these regional disparities. Levels of rural revitalization and development of the 85 counties in Gansu Province show a gradual trend of convergence, indicating a certain degree of stability. These findings support the proposal that rural revitalization and development efforts in Gansu Province formulate precise policies tailored to local conditions to promote coordinated regional rural revitalization.

The current heritage conservation system, fragmented and controlled by administrative units, overlooks the holistic and territorial aspects of heritage resources in China’s Yellow River Basin. Using Moran’s I and kernel density estimation, this study unveils the existing spatial distribution characteristics of heritage resources in the Yellow River Basin up to June 2022. It analyzes the spatial distribution differences in diverse geomorphological, climatic, and aquatic environments through geodetic probes. The findings indicate that: (1) The heritage resources in the Yellow River Basin exhibit notable clustering at various scales. A hierarchical patchy distribution appears at the interprovincial scale, high-value clustering at the intermunicipal scale, and an individual scale distribution pattern, described as three central cores radiating into a belt and four subcores dispersing horizontally. (2) The heritage resources in the Yellow River Basin are concentrated in river valley basins and alluvial plains. The suitable natural environment for their distribution includes warm-temperate climates and a low-altitude (0-849 m) continuous surface (the negative zone) formed by tributaries above the first level of the Yellow River. (3) Within the natural environment, geomorphological elements primarily influence the spatial differentiation of heritage resources in the Yellow River Basin. The positive coupling effect of the slope, river network density, and other factors is noteworthy. The dominant differentiation driving factors include absolute elevation (0.33), geomorphological surface elevation (0.30), and temperature zone (0.18). This study’s results are crucial for comprehending the cultural significance of the Yellow River and fostering the sustainable development of heritage resources.

Based on the China high air pollutants (CHAP) dataset from 2000 to 2023, this study identifies wintertime air pollution events in the urban agglomeration on the northern slope of Tianshan Mountains (Xinjiang, China) using the air quality index (AQI) and analyzes their spatiotemporal patterns (annual mean number of days, annual mean frequency, maximum duration, and intensity). The results demonstrated that (1) PM_2.5 was the dominant air pollutant in the urban agglomeration on the northern slope of Tianshan Mountains, present on more than 95% of the polluted days (AQI>100). (2) A climatological analysis revealed that pollution intensity peaks in the Urumqi-Changji-Shihezi region, where the long-term annual mean AQI exceeds 190 and the annual mean number of days accounts for more than 80% of the winter period. Mild pollution events (101≤AQI≤150) are especially frequent and widespread, with an annual mean of 25.7 days, a maximum annual mean frequency of 17.4 occurrences per year, and a maximum duration of up to 29.0 days. Moderate events (151≤AQI≤200) predominantly occur in the central and eastern subregions, averaging 5 days per year with a maximum annual mean frequency of 14.5 occurrences per year and a maximum duration of up to 12.3 days. In contrast, heavy and severe events (AQI≥201) are concentrated in the Urumqi-Changji-Shihezi region, where AQI peaks can exceed 500. The maximum duration of these events is 11.3 days, exhibiting a “short-duration, high-intensity” evolution pattern. (3) Mild and moderate pollution events have declined in 75.8% of the polluted regions in the urban agglomeration on the northern slope of Tianshan Mountains, but heavy and above pollution events have increased in the Urumqi-Changji-Shihezi core. (4) The characteristics of air pollution events among the nine key cities in the urban agglomeration on the northern slope of Tianshan Mountains varied significantly. Urumqi, Changji and Shihezi are most severely affected, followed by Wujiaqu, Kuytun, and Fukang, while Usu, Karamay, and Bole maintaine the cleanest air. The intensity, annual mean number of days, annual mean frequency, and maximum duration of moderate to severe pollution events in the Urumqi-Changji-Shihezi region are significantly higher than those in other cities, whereas Bole and Karamay are primarily affected by light pollution.

Guanzhong Plain urban agglometration are significant hubs for tourism resources in western China, and the development of its many tourism resources and balanced socioeconomic development require the support of high-speed transport and other infrastructure. In the context of the strategy of a strong transportation country and the development of “transportation and tourism integration”, theoretical research and empirical analysis on promoting the coordinated development of high-speed transportation and the tourism economy can provide support for transforming and upgrading transportation and tourism industries in urban agglomerations. This study focuses on the Guanzhong Plain urban agglometration, utilizing a comprehensive evaluation index system of high-speed transportation and tourism economy. It employs methods such as the entropy value method, the coupling coordination model, and the kernel density function to analyze the comprehensive development of high-speed transportation and the tourism economy. It also analyzes the evolution trend of their coupling coordination over time and space dimensions and examines the differences in the coordinated development of various high-speed transportation modes and the tourism economy. The results show that: (1) The overall comprehensive level of high-speed transportation and tourism economy of Guanzhong Plain urban agglometration is increasing, but a significant developmental difference exists within the city cluster, presenting the phenomenon of uneven development of “one big, and other small”. (2) The high-speed transportation and tourism economy of the city cluster have not yet formed a clear pattern of coordinated development, with their coupling and coordination degree gradually rising over time and evolving to the pattern of “one circle, one axis, and three belts” in space. (3) Large differences exist in the coordination degree of the system and the marginal effect of the tourism economy among different high-speed transportation combinations, and the coupled coordination values of different high-speed transportation modes and the tourism economy differ. Hence, it is necessary to strengthen the overall collaborative effect of the city cluster transportation network, leverage the core driving role of Xi’an City, and accelerate the construction of the Guanzhong Plain urban agglometration high-speed transportation and the coordinated development pattern of the tourism economy.

Objectively understanding the ecosystem services of the Mongolian Plateau and their response to climate factors is of great significance for formulating scientific strategies for ecosystem protection and utilization under the climate change. Based on the data of land use/cover and meteorological observation, this study combined model simulation, spatial analysis and statistical analysis to explore the spatiotemporal patterns of main ecosystem services and theirs relationships with climate factors in the Mongolian Plateau. The results showed that: (1) The habitat quality, water production, carbon storage, and green leisure services of the Mongolian Plateau were high in the east and low in the west, high in the north and low in the south. The air purification service was high in the west and low in the east, high in the middle and low in the surrounding areas. (2) From 2000 to 2020, habitat quality, water yield, carbon storage and green leisure services showed increasing trends with the increase rate of 9.76%, 36.02%, 7.96% and 7.37%, respectively, and the variation of ecosystem services showed an obvious spatial heterogeneity. (3) Climate factors including annual average precipitation, temperature and wind speed are significantly correlated with different ecosystem services. For the whole region of Mongolian Plateau, precipitation contributed most to changes of habitat quality, water yield, carbon storage and green space leisure; wind speed contributed most to the changes of air purification. The contribution of various factors also varied in different subregions. The study comprehensively evaluated the ecosystem status of Mongolian Plateau from the perspective of ecosystem services. The findings could provide scientific reference for China-Mongolia cooperation in ecosystem management to adapt the climate change.

Exploring the impact of territorial spatial ecological protection and restoration on the economic development of China’s poverty-alleviated regions provides valuable insights for promoting sustainable economic development and rural revitalization in these areas during the post-poverty era. Using the double-difference propensity score matching (PSM-DID) model, this study analyzed economic panel data from 58 national-level poverty-alleviated regions involved in the first and second batches of national integrated protection and restoration projects for mountains, rivers, forests, farmlands, lakes, grasslands, and deserts (the “Shanshui Project”) during China’s 13^th and 14^th Five-Year Plans. These were compared with data from 182 non-participating poverty-alleviated regions that had similar natural, social, and economic conditions from 2010 to 2020. This study assesses the impact of ecological protection and restoration on the economic development of these regions. The results indicate the following: (1) Under otherwise unchanged conditions, the economic development rate of poverty-alleviated regions implementing territorial spatial ecological protection and restoration increased significantly by 0.0329 compared to regions that did not implement such measures. This conclusion remains robust after balance tests, parallel trend tests, and placebo tests. (2) In the implementation of spatial ecological protection and restoration, both short-term and long-term economic development effects should be considered. Realizing the value of ecological products is a key driver of sustainable economic development in poverty-alleviated regions. To achieve this, increased policy support is recommended for this region, with a focus on improving systems for realizing the value of ecological products. This approach would enable these areas to successfully transform “green waters and mountains” into “golden mountains and silver mountains”.

Determining the capacity of regional agricultural water resources to support irrigated areas, restraining agricultural water usage, and controlling the expansion of irrigated farmland are crucial strategies for solving sustainable water use problems in the Hexi Corridor of northwest Gansu Province, China. In this paper, we applied the water balance principle and utilized the stepwise regression model to calculate the thresholds of water resource availability and the carrying capacity of the irrigated areas for the Hexi Corridor in different development scenarios. We used information on local water resources, water resource use, and the effective utilization coefficient of irrigation water. The analysis shows the following results: (1) Under the economic priority development scenario, the total exploitable water resources in the Hexi Corridor region is 48.22×10⁸ m³, and the threshold value of the carrying irrigated area is 58.92×10⁴-67.16×10⁴ hm². (2) Under the ecological priority development scenario, the total exploitable water resources are 34.44×10⁸ m³, and the threshold value of the carrying irrigated area is 37.90×10⁴-43.20×10⁴ hm². (3) Under the economic and ecological development scenario, the total exploitable water resources are 41.33×10⁸ m³, and the threshold of the carrying irrigated area is 48.41×10⁴-55.18×10⁴ hm². (4) The proportion of the micro-irrigation area and the effective utilization coefficient of irrigation water have a significant positive correlation. This study can provide a basis for determining a reasonable irrigation area and optimizing the Hexi Corridor’s soil and water planning and distribution system.

To investigate the characteristics of wind farm wake effects and their relationship with meteorological conditions, 33 wind turbines from a wind farm in central Inner Mongolia, China were selected for analysis. Wind resource assessment parameters, including average wind speed, wind direction, and wind frequency distribution, were statistically analyzed from 2021 to 2023. Using the Jensen wake model, wind speeds in the wake area were calculated for different wind directions, with a focus on the refined dominant wind direction. The correlation between wind speeds and meteorological factors, accounting for wake effects, was also explored. The findings are as follows: (1) From 2021 to 2023, the wind farm in central Inner Mongolia was predominantly influenced by southwest winds. High-frequency wind directions shifted from west to south throughout the year. Monthly wind directions were relatively stable, with concentrated wind directions and small wind speed variations. The average wind speed was highest under the dominant wind direction, and the wind speed frequency curve exhibited a positively skewed distribution. (2) Under average wind speeds for each direction, turbines most affected by the wake experienced wind speed losses exceeding 10%. More than half of the turbines were affected by wake effects under northwest and southeast winds, with the most significant losses occurring in the northeasterly downstream positions of the wind farm. Wind speed reductions were particularly pronounced under westerly winds. (3) The impact of barometric pressure, air temperature, and humidity on daily wind speed variation differed across wind directions. For southwest winds, the wake model performed best in the 4-5 m·s^-1 wind speed range, with the average absolute percentage error of wind speed negatively correlated with relative humidity. For northwest winds in the 9-10 m·s^-1 range, the wake model calculations closely matched measured wind speeds, with errors positively correlated with barometric pressure and temperature. In addition, the wake model performed well in the 9-10 m·s^-1 and 7-8 m·s^-1 ranges for southeast and northeast winds, respectively. These results provide valuable insights into the analysis of wind turbine wake effects and wind speed predictions for wind farms.

The primary goal of green development is to improve the overall welfare associated with sustainable practices. The digital economy has a dual effect on regional green development. This study systematically analyzes the theoretical mechanisms through which the digital economy influences green development welfare. An empirical assessment was conducted using panel data from 36 resource cities in the Yellow River Basin for the years 2013 to 2022, employing both the double-fixed effect model and spatial Durbin model. The findings indicate that: (1) Regarding spatial and temporal evolution, the overall level of green development welfare is relatively low, showing a gradual upward trend over time, with a spatial distribution pattern characterized by medium and low levels, supplemented by a few high-level points. (2) The digital economy significantly enhances the level of regional green development welfare among resource cities in the Yellow River Basin, and this effect remains robust under testing. (3) Regarding heterogeneous effects, the digital economy plays a particularly important role in promoting welfare in growing resource cities. (4) Analysis of spatial spillover reveals that the digital economy has a positive spatial spillover effect on green development welfare, with both direct and total effects being significantly positive, although the indirect effect is significantly negative. These results can assist the region in synergizing the digital economy with green development welfare, thereby promoting a form of Chinese-style modernization that fosters harmonious coexistence between human beings and nature.

Railways are vital external transportation infrastructures in modern cities and play an important role in urban development. However, they also cause certain negative impacts, such as the fragmentation of urban patterns and disruption to residents’ lives. The study focused on Lanzhou City, Gansu, China, a linear city, and investigated the not-in-my-backyard (NIMBY) impacts of railway facilities employing a price characteristic model and a geographically weighted regression model. The study concluded the following. (1) Railway facilities significantly reduce housing prices. With every 1% reduction in distance between railway and railway stations, housing prices fall by 0.175% and 0.017%, respectively. (2) The NIMBY influence ranges approximately 1.2 km from the railway and approximately 0.6 km from the railway station. Owing to Lanzhou’s linear urban layout (a belt along the same direction), which runs parallel to the railway, several residential blocks (55.24% of total housing in the city), are within the NIMBY-affected area. (3) The spatial effects of the railway and railway stations vary significantly. Houses closer to the city center, particularly those related along the inner side of the railway, experience greater negative impacts. Furthermore, development areas are more impacted by the railway, and properties in high-price areas are more strongly affected compared to those located in the suburbs. (4) The “dock area” surrounding railroad stations has a maximum influence of 1.6 km, while the “municipal support area” affects up to 0.8 km. This implies that the positive effect of the station has a significant offsetting effect on the NIMBY effect.

In the context of complex risks and regional synergy, exploring a multi-center, multi-level, and multi-node resilience spatial network structure for the resilience building, risk prevention, and sustainable development of urban agglomerations holds significant practical value. This study applies social network theory and uses the three major urban agglomerations in the Yellow River Basin as a case study. The modified gravity model calculates the spatial correlations of urban resilience development, and based on this, social network analysis is employed to evaluate the structural characteristics of the resilience spatial association network in these urban agglomerations. The findings reveal the following: (1) The resilience level of the three major urban agglomerations in the Yellow River Basin is trending upward, with increasing intensity in network connections, indicating that the overall resilience network is becoming more robust and integrated. (2) The spatial connectivity of resilience among the urban agglomerations is tightening, with provincial capitals demonstrating a strong radiation effect and holding dominant positions, although development among sub-agglomerations remains uneven. A typical network-type spatial pattern has emerged, where the Shandong Peninsula urban agglomeration forms a resilient spatial network characterized by “one main and two subordinate” centers, with Jinan City as the central node and Qingdao City and Yantai City as secondary centers. The Central Plains urban agglomeration forms a “radial” resilient spatial network with Zhengzhou City as the center and Kaifeng City, Luoyang City, and other cities as secondary centers. The Guanzhong Plain urban agglomeration shows a closely interconnected resilience network, presenting a “dual-core” spatial pattern linked by the provincial capitals of Xi’an City and Xianyang City.

The analysis of the spatial and temporal variations in potential evapotranspiration and its sensitivity to meteorological factors in different dry and wet zones is essential for optimizing water resource management in agriculture, animal husbandry, forestry, and water resource planning and allocation, as well as for predicting the impact of climate change on water resources. Given the diverse dry and wet conditions and climatic conditions in Inner Mongolia, China, a region significantly affected by climate change, the sensitivity coefficients of potential evapotranspiration to air temperature, wind speed, water vapor pressure, and sunshine hours were calculated based on the Penman-Monteith formula of the FAO for 76 meteorological stations in Inner Mongolia from 1961 to 2023. The dominant factors influencing potential evapotranspiration in different dry and wet zones and its quantitative response to climate change were investigated. The results indicate that: (1) Spatially, potential evapotranspiration generally decreases from west to east in the longitudinal direction and from south to north in the latitudinal direction. In arid and semi-arid zones, the trend in potential evapotranspiration is not pronounced, whereas in semihumid zones, an increasing trend is observed. (2) The sensitivity of potential evapotranspiration to meteorological factors follows this order: maximum air temperature is the most sensitive factor, followed by water vapor pressure, wind speed, and minimum air temperature, with sunshine hours being the least sensitive. (3) The sensitivity coefficients of all meteorological factors exhibit consistent trends across different dry and wet zones. The temperature sensitivity coefficient and vapor pressure sensitivity coefficient show a decreasing trend, whereas the wind speed sensitivity coefficient and sunshine hours sensitivity coefficient display an increasing trend, with significant changes observed for the water vapor pressure sensitivity coefficient and wind speed sensitivity coefficient. (4) Maximum and minimum air temperatures contribute positively to changes in potential evapotranspiration, whereas wind speed, water vapor pressure, and sunshine hours contribute negatively. Among these, sunshine hours have the least influence on potential evapotranspiration in all dry and wet zones. Wind speed is the dominant factor driving potential evapotranspiration changes in arid and semi-arid zones, while maximum air temperature is the dominant factor in semihumid zones.

This study analyzes daily temperature data from 38 meteorological stations in Xizang, China, covering the period from 1981 to 2023. A new method for seasonal division in Xizang was employed to categorize the four seasons, and the regional climate changes, temporal shifts in the start dates of each season, and trends in seasonal changes were examined. The results show the following. (1) Areas with four distinct seasons in Xizang are primarily found along the Yarlung Zangbo River and in Nyingchi City, whereas regions with less distinct seasonal variations (including areas without a summer season) are mainly situated in the western and northern parts of Xizang as well as in the high-altitude regions of the Himalayas. (2) In Xizang, the beginning of spring and summer tends to occur earlier, whereas the onset of autumn and winter tends to be delayed. Notably, the start date of spring was significantly earlier in 2000, whereas the onset of autumn and winter was significantly delayed in 2003 and 1995, respectively. (3) Regarding the timing of seasonal starts, the first empirical orthogonal function (EOF1) for spring and autumn exhibited a pattern of “northwest low and southeast high in spring, and middle high and both sides low in autumn”. In spring, the second EOF (EOF2) presented a contrasting distribution pattern of “northwest positive and southeast negative”, whereas in autumn, EOF2 showed an opposite spatial distribution pattern characterized by “southwest positive and northeast negative”. The EOF1 in winter revealed a “high in the north and low in the southwest” pattern, whereas the EOF2 shared similarities with that of spring’s EOF2. (4) Looking ahead, we anticipate that the start dates of spring and summer will be delayed, whereas those for autumn and winter will be advanced.

Understanding the coupled coordination of new urbanization and agricultural modernization (the “two modernizations”) in China's Yellow River Basin is important for promoting ecological protection, high-quality development, urban-rural integration, and coordinated regional development in the region. This study quantitatively analyzes the levels and spatiotemporal patterns of the “two modernizations” in 67 prefectures of the Yellow River Basin from 2010 to 2022 and examines the related mechanisms. To this end, an index system is constructed, and the entropy method, coupling coordination degree, and geographic detector method are employed for analysis. The results show the following: (1) During the study period, the level of the “two modernizations” in the Yellow River Basin increased significantly, showing a spatial distribution pattern of high in the east and low in the west. (2) The type of coupled coordination of the “two modernizations” has evolved from being mostly disorderly to being dominated by reluctant coordination, with the scope of primary and secondary coordination steadily expanding. (3) There is considerable spatial agglomeration in the coupled coordination of the “two modernizations”. For instance, a core area of extreme hotspots has formed in Shandong Province, while two cold-spot agglomeration areas have emerged in Shanxi Province and Gansu-Ningxia Provinces. (4) The spatial differentiation pattern of coupled coordinated development is the result of synergies and interactions among multiple factors. Core drivers include the economy, the market, and digital finance. Agri-tech and income are secondary drivers, while transportation significantly interacts with other factors. This study strengthens our theoretical understanding of the coupled coordination of the “two modernizations” and provides a policy reference for promoting new urbanization, agricultural modernization, and integrated urban-rural development in the region.

Scientific planning of public cultural facility layouts is essential for enhancing public cultural service systems and addressing the population’s demand for a high-quality spiritual life. Utilizing point-of-interest (POI) data and the ArcGIS 10.8 software platform, this study employs methods such as mathematical statistics, nearest neighbor index, kernel density estimation, and geographical detectors to analyze the spatial structure and influencing factors of public cultural facilities in Inner Mongolia of China across multiple scales. The results indicate the following: (1) At the provincial scale, public cultural facilities are unevenly distributed, exhibiting significant gaps and clustering patterns across various facility types. High-density areas are concentrated in the south, while low-density areas dominate the north, with the “Alagxa Left Banner-Jalaid Banner” line serving as a demarcation. (2) At the regional scale, distributions in west, central, and east Mongolia are clustered, displaying pronounced inequities. Central Mongolia surpasses east and west Mongolia significantly in the number and density of public cultural facilities. (3) At the league and city scale, facility numbers vary markedly, with the “Hohhot-Baotou-Ordos” region demonstrating a high degree of clustering, followed by Wuhai, Ulanqab, and Bayannur cities. Clustering diminishes slightly in Chifeng City, Tongliao City, and Hinggan League and is even weaker in Xilin Gol League and Hulun Buir City. Alagxa League displays a scattered distribution. (4) The spatial structure of public cultural facilities in Inner Mongolia arises from the synergistic interactions of economic, cultural, social, and natural factors. These interactions generate nonlinear enhancement or dual-factor enhancement effects, producing outcomes where “1+1>2”.

In order to evaluate the soil quality status of farmland in Shawan City of Xinjiang, China and to clarify the key influencing factors on productivity level, and promote the construction of high standard farmland in Shawan City, this paper build the minimum dataset of farmland soil quality with principal component analysis and cluster analysis, and combined with an obstacle factor diagnostic model, the characteristics and obstacle factors of agricultural soil quality in the Shawan area were revealed. The results led to three main conclusions. (1) There were significant differences between the results of soil quality evaluations using different datasets. The soil quality indices determined using the minimum dataset based on cluster analysis and using the total dataset significantly positively correlated (R²=0.591, P<0.1),the Nash effective coefficient was -4.923, indicating that the minimum dataset based on cluster analysis gave better results than the minimum dataset based on principal component analysis. This indicated that the minimum dataset based on cluster analysis was more suitable than the minimum dataset based on principal component analysis for replacing the total dataset when evaluating farmland soil quality. (2) The overall soil quality in the study area was found to be moderate and better, and the soil quality indices were 0.130-0.641. Farmland in Shawan City was divided into five classes using the soil quality index minimum dataset. Class I soil was mainly in the northern and northwestern parts, and class V soil was mainly in the southeastern part of the study area, indicating that the soil quality was generally high in the northwest and low in the southeast. (3) There were obvious obstacles in the research area, which low organic matter contents, insufficient nitrogen, and high electrical conductivities were the main obstacles. The research results can be used to effectively improve the soil quality of local farmland. It is recommended that in the process of farmland management, not only applying organic fertilizer, take measures such as deep tillage, planting weeds, covering straw, and plastic film to improve the soil.

To investigate the pollution characteristics of PM_2.5 in the middle Tianshan Mountains, PM_2.5 samples were collected in Wulasitai region of the middle Tianshan Mountains from July to September 2019. Heavy metal contents were analyzed using inductively coupled plasma-mass spectrometry (ICP-MS), while polycyclic aromatic hydrocarbons (PAHs) were examined using gas chromatography-mass spectrometry (GC-MS). The study explored the sources and health effects of heavy metals and PAHs in PM_2.5. The key results are as follows: (1) Concentrations of heavy metals and PAHs during summer and autumn in the middle Tianshan Mountains were relatively low. The average concentration levels of each element were: Fe>Cu>Zn>Pb>Mn>Cr>As>V>Rb>Ni>Co>Se>Cd>Tl. The total average heavy metal concentration was 238.50 ng·m^-3, with Fe (139.90 ng·m^-3) and Cu (78.72 ng·m^-3) being dominant, while other elements were below 10 ng·m^-3. The total average concentration of PAHs was 1.37 ng·m^-3, with 3-ring, 4-ring, and 5-7 ring PAHs concentration accounting for 3.59%, 32.34%, and 64.07%, respectively. (2) During the observation period, PM_2.5 was influenced by long-distance transport from the west and short-distance transport from the north and west. It may also have been affected by local valley wind and boundary layer changes. (3) Positive matrix factorization (PMF) identified key pollution sources, including natural gas combustion and petroleum sources (28.56%), vehicle emissions and coal burning (28.46%), biomass burning and industrial pollution (16.14%), non-ferrous metal smelting (14.32%), and dust (12.52%). (4) Direct inhalation of PM_2.5 posed a carcinogenic risk to adults and children due to heavy metals and PAHs, with Cr, Co, As, and Se identified as high-risk substances. Non-carcinogenic health risks were relatively low.