Refinement governance is the future governance direction of the city, and it is also an important challenge for Shanghai to build an outstanding global city. Most of the existing research is based on the innovative mode and management mechanism of urban grid management, but the analysis and mining of grid management event data are still insufficient, and there is a lack of regular analysis of meteorological conditions on the occurrence of events. From the meteorological perspective, this paper uses spatiotemporal feature analysis and natural language processing methods to analyze the features of grid management event data, and uses correlation analysis and frequent pattern mining algorithms to obtain the association rules between meteorological conditions and urban management events. On this basis, the typical meteorological conditions that trigger grid management events are obtained, and the typical event knowledge graph covering meteorological conditions is constructed. The results show that the events are highly correlated with the characteristics of residents’ activities, the occurrence time of events is highly consistent with the working time, and the occurrence area also coincides with the densely populated areas of the city. There is a phenomenon of “concentrated head and long tail distribution” in the category, and a clear clustering structure can be formed in the event word segmentation, forming a co-occurrence term relation network with citizen activities as the main body. Analysis with meteorological data, municipal facilities and sanitation categories have obvious correlations with air temperature, wind-vulnerable structures are greatly affected by wind, and some illegal behaviors are also highly correlated with meteorological conditions. In addition, under specific weather conditions, some events will show an obvious tendency to occur easily. For example, events such as foundation pits, disputes, high-altitude parabolas, and river greening occur under specific weather conditions such as precipitation, low temperature, high temperature and strong wind, and strong winds will also have an amplified effect on environmental problems such as river pollution, open burning and the distribution of leaflet. On this basis, the knowledge graph technology is used to summarize and express the relationship between meteorology and urban operation, so as to form a knowledge framework for urban operation signs triggered by meteorological conditions, which is beneficial for urban operation managers to respond and deal with specific weather conditions in advance, and provide certain decision-making references for Shanghai to improve refined management measures and optimize the urban governance system.

In the era of digitalization, it is of great practical significance to explore the spatial network structure of digital economy and its driving factors for promoting the construction of “digital China”. The research applied the modified CRITIC evaluation method to measure the development level of digital economy of China from 2013 to 2020, and explored the evolution characteristics and causes of the spatial network structure of the digital economy by social network analysis. The results show that: 1) The overall level of digital economy development has shown a steady upward trend, and the spatial pattern is characterized by high in the east and low in the west. 2) During the study period, the spatial connection network of the provincial digital economy in China shows a complex situation of multi-threaded and dense networking. The network density is improved, and there is no hierarchical spatial structure as a whole. 3) The economically developed regions have a significant advantage in the spatial network structure, and the connections between the western and border regions and other regions needs to be improved; the condensed subgroup spatial distribution gradually forms an orderly agglomerated distribution. 4) The spatial correlation network of digital economy is affected by the joint action of multiple factors. The level of scientific and technological innovation, government support and geographical distance have always played a significant role, while the effects of economic development level, industrial structure level and urbanization level reflect the stage characteristics by strong first and weak later. The above factors together drive the optimization and restructuring of the provincial digital economy spatial network structure in China.

A striking warming trend has triggered extreme weather and events in the regions worldwide. Snowfall is an important indicator of climate change, changes in snowfall at different levels reflect the integrated response of global warming to the trends in key climate variables and extreme events, and significant geographical variation exists in the response pattern of snowfall in different levels across regions. Mountainous areas are highly sensitive to climate change. As an important geographical demarcation line between the north and south of China, the Qinling Mountains belongs to China’s snow-frequent belts, a sensitive area under climate change. Based on the daily data from the 72 meteorological stations, we analyzed the spatio-temporal variation of heavy snowfall and light snowfall during November-March of the following year in the south and north of Qinling Mountains from 1970 to 2018, using the method of the wet bulb temperature dynamic threshold and trend analysis. Moreover, we assessed the relationship between the snowfall and temperature in three sub-regions (Guanzhong Plain, south slope of Qinling Mountains and Hanjiang Valley). The results show that: 1) From 1970 to 2018, the number of rainless days increased, and the solid precipitation decreased obviously during November-March of the following year in the south and north of the Qinling Mountains. The number of snowfall days decreased from 8.5% to 5.2% in the previous period after 1998, and the proportion of sleet days decreased from 1.2% to 0.6%. 2) The response patterns of snowfall to climate change varies from snowfall in different levels. The snowfall amount and snowfall days of light snowfall decreased significantly, as well as intensity of light snowfall increased significantly. However, there was no clear linear increasing tendency in the snowfall amount, snowfall days and intensity of heavy snowfall, which indicates that the change of snowfall in the transition zone between north and south of China is dominated by the decrease of light snow. 3) In terms of the response to the temperature, the snowfall amount and days of light snowfall in the three sub-regions were significantly negatively correlated with temperature changes (P<0.05). Similar results were observed in the snowfall amount and days of heavy snowfall days in Guanzhong Plain and Hanjiang Valley. Meanwhile, three indexes of heavy snowfall were weakly correlated with the temperature of the south piedmont of the Qinling Mountains. Both Guanzhong Plain and Hanjiang Valley are the sensitive area the response of heavy snowfall to the temperature. The findings of this research can provide a theoretical basis for better understanding the winter climate response pattern in winter in the transitional zone between the north and south of China.

Resource-based cities (RBCs) are a unique type of cities in China that have significantly contributed to China’s national economy. However, the development of RBCs has encountered challenges, and their transformation and development require urgent attention due to the depletion of resources in RBCs and the need to comply with national ecological environment protection requirements in the 21st century. To explore the hotspots and frontiers of RBCs’ transformation and development, this paper analyzes 602 CSSCI journal papers published between 1999 and 2021. The research distribution was analyzed from 3 aspects: time, journal and author distribution, using software such as CiteSpace, VOSviewer, Data source, scientific knowledge graph. The paper explores the overall situation from evolution, hotspots and frontier. The conclusions are as follows: 1) The transformation and development of RBCs has gradually entered the Chinese government’s and academia’s vision since the 1980s, but substantive research only began in 2004. 2) From a time distribution perspective, research on the transformation and development of RBCs in China can be roughly divided into 3 periods: slow exploration period (1980s—2003), high-speed growth period (2004—2013) and steady progress period (2014—); In terms of journal distribution, China Population, Resources and Environment, Economic Geography, Journal of Natural Resources, Geographical Research and Scientia Geographica Sinica are notable journals that significantly supported and led studies on RBCs. Regarding authorship, the study found that Yu Jianhui, Qiu Fangdao, Zhang Wenzhong and Jiao Huafu have had great influence and contribution in this field. 3) The study also identified 6 research frontier trends: green transformation and development of RBCs, population shrinkage of RBCs, carbon emissions of RBCs, spatial reconstruction of RBCs, innovation and transformation development of RBCs, comprehensive management of two special difficult areas of coal mining subsidence areas and independent industrial and mining areas. Finally, the study proposed future research directions in four aspects: high-quality development of RBCs, smart development of RBCs, carbon emission reduction of RBCs and spatial development of RBCs.

Under the new round of technological revolution and industrial transformation, it is crucial to vigorously develop digital technology. This paper defines digital technologies using patent data and employs them as a measure of urban digital technology innovation. Spatial statistical and econometric methods are used to reveal the temporal evolution, spatial evolution, and influencing factors of digital technology innovation in Chinese cities. The results are as following: 1) The scale of digital technology innovation in China presents a monotonically increasing trend driven by multiple factors such as demand and policies, with the innovation scale of 7 subdivided fields maintaining a relatively stable hierarchical pattern. 2) There are significant spatial differences in digital technology innovation across Chinese cities. Its evolution exhibits a notable trend of agglomeration and diffusion coexistence, forming a digital technology innovation pattern with the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD) urban agglomerations as the core drivers, provincial capitals and sub-provincial cities as multi-point supporters. The spatial evolution of innovation in the 7 digital technology fields shows a similar process of diffusion from core cities to peripheral cities. The outputs of all types of digital technologies are highly concentrated in leading cities like Beijing, Shanghai, and Shenzhen, but the main city compositions for different types of digital technologies differ slightly. Some cities with overall middle-to-high rankings demonstrate relative comparative advantages in specific digital technology fields. 3) The influencing factors of digital technology innovation in Chinese cities exhibit significant spatial spillover characteristics. Knowledge bases and technology introduction are important factors promoting local digital technology innovation. However, the role of institutional factors in driving local digital technology innovation remains to be highlighted. Neighboring regions’ explanatory variables usually have a reverse impact on local digital technology innovation due to the suction effect or a unidirectional impact due to the spillover effect. The heterogeneity analysis shows that the influencing factors for the 7 digital technologies exhibit both similarities and heterogeneities.

Taking Shandong Province as an example, this article uses the net carbon sequestration accounting model and Kuznets Curve and other methods to calculate the net carbon sequestration of cultivated land use in 16 cities in Shandong Province from 2001 to 2020, and clarifies the relationship between the spatiotemporal changes of net carbon sequestration of cultivated land use and the economic and social benefits of cultivated land. The results show that: 1) From 2001 to 2020, cultivated land in Shandong Province played a huge role as a carbon sequestration, and the net carbon sequestration showing a fluctuating upward trend. In 2020, the net carbon sequestration of cultivated land use in Shandong Province increased by 33.052%, which has exceeded one-ninth of the national total. 2) The net carbon sequestration of cultivated land use in Shandong Province has exhibited significant spatial heterogeneity characteristics, presenting a spatial pattern of high in southwest and low in northeast. In 2020 alone, the high-value area of net carbon sequestration was 13.743 times that of the low-value area. 3) There exists an upward-downward-upward “N” shaped Kuznets curve relationship between the net carbon sequestration of cultivated land use and the output value of cultivated land per unit area in 16 cities in Shandong Province. 4) There is a significant inverted “U” shaped Kuznets curve relationship between the net carbon sequestration of cultivated land use and the per capita disposable income of rural residents in 16 cities in Shandong Province. The spatiotemporal changes of net carbon sequestration in cultivated land use have a significant responsive relationship with the economic and social benefits of cultivated land use.

In recent years, the focal point of policy attention has revolved around how to adapt to new circumstances and implement regional optimization and spatial governance. Chinese government has recently emphasized the construction of a series of well-connected suburban new cities, aiming to drive the development of polycentric urban centers and suburbanization. Consequently, the current policy emphasis is on advancing the rational layout of internal urban spaces through planning and governance, optimizing the internal spatial structure of cities. From a practical perspective, over the past two decades, the internal spatial structure of most Chinese cities has indeed undergone a transition from a single center to multicenter. While factors influencing the internal spatial structure encompass aspects like natural endowments, economic levels, public services, and transportation conditions, the research on these influencing factors has been insufficient due to data limitations and the complexity of real-world issues. Simultaneously, significant transformations have occurred in China’s highways over the past two decades. Numerous studies have confirmed their crucial role in promoting regional coordinated development and reshaping urban systems. However, there has been a prolonged neglect of the impact of highways on the internal spatial structure of cities. Against this backdrop, this study, utilizing the analysis framework of the urban polycentric spatial structure model, specifically elucidates the impact mechanism of highways on the polycentric spatial structure. Simultaneously, based on high-resolution global population distribution data from LandScan from 2001 to 2019, we constructed multiple sets of indicators for the polycentric spatial structure. Employing historical transportation routes, planned routes, and other instrumental variables, we systematically identified the impact effects of highways on the polycentric spatial structure. The results show that: 1) Polycentric spatial structure has become a primary development trend within China’s urban areas. 2) Ray-shaped or peripheral transit highways can enhance the regional advantages of peripheral areas and accelerate the transformation of spatial structure from monocentric to polycentric by agglomeration of land, development zones, enterprises, and population factors. 3) Large cities, eastern and southern cities and cities with low government financial capacity are more effective in shaping polycentric spatial structure of highways. The approach provides insights into using spatial big data technology for researching urban economics issues. The study’s conclusions supplement empirical evidence on the role of transportation infrastructure construction in promoting factor mobility and shaping spatial structures. The study holds significant policy implications for further optimizing the layout of transportation infrastructure, exploring the advantages of polycentric spatial structures, and enhancing urban economic and population carrying capacity.

High latitude permafrost regions are the most sensitive areas to climate change. The degradation of permafrost seriously affects the soil carbon cycling process. Revealing the vertical distribution pattern of soil organic carbon in permafrost layers under different land cover types is of great significance for predicting future changes in soil carbon pools in permafrost regions. Here we select forests, forest swamps, and shrub swamps in the high latitude permafrost areas of the Da Hinggan Mountains. Soil columns (7-8 m) were collected using drilling methods to measure soil carbon (organic carbon, soluble organic carbon) under the three different land types, and further analyzed the carbon content at different depths. The results showed that as the depth increased, the soil carbon contents decreased, and the organic carbon content varied from14.55 g/kg to 95.98 g/kg (forest swamp), from 17.48 g/kg to 132.93 g/kg (forest), and from 2.58 g/kg to 396.50 g/kg (shrub swamp). There was also a high carbon content soil layer in permafrost layers. The average content of organic carbon and soluble organic carbon in the active layer soil is as follows: shrub swamp>forest>forest swamp, and the average content of organic carbon and soluble organic carbon in the permafrost layer soil is as follows: forest swamp>forest>shrub swamp. The correlation analysis revealed significant negative correlations between depth and soil organic carbon content, water-soluble organic carbon content, and soil water content in soils under forest and shrub swamp conditions. However, there was no significant correlation between depth and these indices in soils under forest swamp conditions. Additionally, pH values were significantly positively correlated with depth across all soils, while they were negatively correlated with soil organic carbon content, soluble organic carbon content, and soil water content. The coefficient of variation of organic carbon in the active layer is 30.31%-114.26%, and the coefficient of variation of organic carbon in the permafrost layer is 30.23%-192.09%. Correlation analysis showed that soil organic carbon was negatively correlated with depth and pH, and significantly positively correlated with soil moisture.

To compensate for the limitations of case fragmentation, inconsistent standards, misused methods of identifying city centers, and incomparable conclusions in the established Chinese polycentric spatial structure studies, this study aimed to identify all the city (sub)centers of 297 Chinese prefecture-level or above cities in 2019 by using fine-grained Landscan ambient population data and integrating spatial autocorrelation analysis with polycentric regression models. We also measured the degree of urban polycentricity using three indicators: the number of city centers, the relative distance between city centers, and the balance of center development. Then, we summarized ten types of urban spatial structure patterns based on the combination of the three polycentricity indicators mentioned above. The study identified a total of 863 centers in 297 prefecture-level or above cities in 2019, and learned the theoretical density and density gradient of each center in every city through the negative exponential function. These findings served as a comprehensive examination of the underlying base map of the polycentric structure of Chinese cities and formed the basis for subsequent longitudinal tracking analyses. Our study revealed that in 2019, monocentric, bicentric and polycentric cities accounted for approximately 29%, 20% and 45% of the total, while 5.7% of the cities remained in a dispersed pattern. We found that, except for a few cities with a dispersed pattern, the more centers, the fewer the corresponding cities. Developed, mountainous, provincial border cities, and small and medium-sized cities with an evenly distributed urban population were more likely to form sub-centers far from the main center. Larger cities with a cluster layout and smaller cities with strong counties but weak districts were more likely to develop multiple (or dual) centers with equal density and balanced influence, while the main center of circle-sprawling cities tended to dominate the population distribution in the whole region, and their spatial patterns showed a polarized trend. Our study demonstrated that the level of social and economic development was the primary factor in shaping the polycentric spatial structure of Chinese cities, and the fluctuation and variability of natural topography also objectively contributed to the growth of urban polycentricity. However, out-migration public policies such as government relocation and the construction of industrial development zones and new town did not have a significant effect on urban polycentricity. It was also difficult for road construction to effectively promote the growth of new sub-centers. Therefore, the polycentric spatial structure was the product of high-level socio-economic development rather than an artificial creation through leapfrogging planning.

Taking the metro station domains in the main urban area of Hefei as an example, this study analyzed its spatial vitality characteristics based on multi-source data such as the Baidu heat index. A random forest model was used to measure the correlation of six built environment elements, including geographic location, land use, functional facilities, development intensity, accessibility, and environmental quality, with the spatial vitality of metro station domains. Furthermore, combined with the K-means clustering algorithm, this study classified the types of metro station domains and identified the deficiencies of typical station domains, and then proposed spatial vitality optimization strategies for different types of metro station domains in a targeted manner. The results show that: 1) The spatial vitality of the metro station domains in the main urban area of Hefei was higher in the evening peak than in the morning peak, and higher in the evening peak on weekdays than in the evening peak on weekends. Spatial vitality also showed a differentiation pattern of “high inside and low outside”, with vitality values decreasing from the second ring road to the outside; 2) The relative importance of each built environment variable on the spatial vitality of metro station domains during the morning, evening, and off-peak hours on weekdays and weekends was ranked in descending order: functional facilities>development intensity>geographic location>land use>accessibility>environmental quality; 3) The metro station domains in the main urban area of Hefei were divided into 4 types: mature, growing, low maturity and breeding, showing the significant clustering characteristic of “circle structure”. The mature-type station domains were clustered within the second ring road, the growing-type station domains were distributed in a circular pattern along the second ring road, the low maturity-type station domains were mainly scattered outside the second ring road in the Binhu District and the Economic Development District, and the breeding-type station domains were mainly distributed outside the second ring road in various districts of the city with a wide range. The study aims to provide policy insights for the enhancement of spatial vitality of metro station domains and low-carbon transportation strategies from a built environment perspective.

With the intensification of climate change and the rapid development of the economy and society, the uneven distribution of water resources in time and space and the contradiction between supply and demand in the urban agglomeration in the Yellow River Basin have become increasingly prominent, exposing the problem of interactive stress between the ecological environment in the basin and urban development. High-quality development in the Yellow River Basin represents an advanced stage of sustainable development, and sustainable utilization of water resources in urban agglomerations creates more room for improvement in high-quality development. To actively respond to the Sustainable Development Goals proposed by the United Nations, this study takes five national urban agglomerations in the Yellow River Basin as the research object and uses the water footprint and related evaluation indices to construct an evaluation framework of the water resource utilization level oriented to Sustainable Development Goal 6. This framework is used to evaluate the water resource utilization and protection level of urban agglomerations in the Yellow River Basin. The dynamic change characteristics of the water footprint of the Yellow River Basin urban agglomeration from 2010 to 2019 are described based on the total water footprint and the proportion of each account, per capita water footprint, water footprint intensity, and water planet boundary. Global and local Moreland indices are used to describe the spatial evolution characteristics of the water footprint of the Yellow River urban agglomeration from 2010 to 2019. Based on an analysis of the spatial and temporal evolution characteristics of the water footprint of urban agglomerations in different sections of the Yellow River Basin, spatial econometric models of urban agglomerations in the whole basin, the upper and middle reaches and the lower reaches are established. This paper discusses the similarities and differences in the driving effects of socioeconomic factors on the water footprint in different sections of the basin; these factors include gross regional product, permanent resident population at the end of the year, population density, total investment in fixed assets, foreign direct investment, built-up area, total import value and total export value. The results show that the total water footprint and mean value of urban agglomeration in the Yellow River Basin increase from the upper reaches to the lower reaches in a cascade distribution pattern, with significant regional differences. The water footprint and its related indicators show an overall downward trend, but there is still a certain gap in achieving Sustainable Development Goal 6. The water footprint of urban agglomerations in the upper and middle reaches and the lower reaches presents a polarization state of “low-low” agglomeration and “high-high” agglomeration, respectively, and transitions to “low-low” agglomeration on the whole. The driving factors in different urban agglomerations have significant differences and spatial interaction effects. Therefore, countermeasures and suggestions are proposed to strengthen the radiative driving role of central cities, improve the resilience of urban water resource ecosystems, and implement differentiated water resource system management according to the comparative advantages of different urban clusters. These suggestions provide a scientific basis for strengthening watershed system governance.

Snow cover changes in the middle (2035—2064) and end (2070—2099) of 21st century are investigated over the Qinghai-Tibet Plateau based on the Historical data and ScenarioMIP data of the Coupled Model Intercomparison Project Phase 6 (CMIP6). Compare with the reference period (1985—2014), the mean annual snow cover days and mean snow duration decrease during the middle and end of the 21st century over the Qinghai-Tibet Plateau, and the overall reduction are more pronounce with the increase of greenhouse gas emission concentration; the reduction in the late-21st century is more pronounced compare to the mid-21st century except for the low emission scenario; Spatially, the decrease in the southeast of the Qinghai-Tibet Plateau is more severe than that in the northwest. The snow onset date is delayed and the snow end date is advanced in the middle and late 21st century, the days of former is 1.5-2.0 times that of the latter; The more greenhouse gas emissions the more days the snow onset (end) date is delayed (advanced); The changes of the snow onset date and the snow end date are more pronounced in the late 21st century. Snowfall (temperature) is positively (negatively) correlated with the annual snow cover days; Generally ,the relative contribution rate of snowfall to the annual snow cover days increases with the increase of greenhouse gas emission concentration; Spatially, snowfall (temperature) contributes more to the annual snow cover days in the southern and northern (east and west) parts of the Qinghai-Tibet Plateau. Decrease in snowfall from July to December is greater than from January to June, which may be the reason why the days of snow onset date is delayed more than the days of snow end date is advanced. There are great differences in the future snow cover changes over the Qinghai-Tibet Plateau under different scenarios, so controlling greenhouse gas emissions is crucial to slowing down the future snow cover reduction rate over Qinghai-Tibet Plateau.

The South China Sea Rim region is the anchor of China’s “21st Century Maritime Silk Road” initiative. It is of great significance to clarify the regional aviation connectivity and its development mechanism to promote economic and trade cooperation among countries. To this end, this paper attempts to describe the spatial evolution of the regional airline network around the South China Sea and reveal its self-organization development mechanism by constructing an aviation connectivity index, using the dominant flow and TERGM models. The results are as follows: First, the aviation hub hierarchy in the South China Sea Rim region maintains a basic stability and a certain degree of mutation. The capitals of ASEAN countries with Singapore, Kuala Lumpur, Jakarta, Bangkok, and Manila as the core, as well as Hong Kong, Guangzhou and other cities are the aviation hubs of the South China Sea Rim region. Second, the connection within the South China Sea Rim region is stable in the Indonesia-Malaysia-Thailand triangle, and it is spreading to the coastal cities of China and the Philippines in the east. The hub-and-spoke organization presents a multi-center evolution trend, following the law of regional agglomeration. Finally, the closed ternary structure has a positive effect on the air connection, the air connection of non-core cities expands rapidly, and the low-level nodes show a trend of active expansion in the process of network evolution. The urban economic development, city size, institution, culture and cooperation events all have positive impacts on air passenger transport enhancement, while geographical distance and the conflict events have a negative impact on air connections, and the overall network presents a gradual development trend.

With the implementation of the “double reduction” policy and the advent of the post-epidemic era, the status of family education has become increasingly important. Based on the data from the 2020 questionnaire survey, this paper uses factor analysis, hotspot analysis and other methods to interpret the socio-spatial differentiation of the family education environment at the compulsory education stage and its impact on the in-home learning experience. It is found that: 1) There is multi-scale spatial differentiation in the family education environment. First, the highest degree of differentiation is found among families, reflecting the dominant role and great differences between families in constructing the family education environment. Second, the differentiation between urban circles is obvious, and the family education environment in the urban core area is more advantageous than that in urban suburbs and urban new areas. Thirdly, the differentiation and decentralized clustering of family education environments among residential and school districts also requires attention. The differentiation of the family education environment is the result of a combination of different scale factors, such as the urban environment, school districts, and residential neighborhoods and families. 2) The characteristics and spatial distribution of family education environments differ significantly among different groups. High-socioeconomic-status families provide a high-quality family education environment with the highest comprehensive score and the highest scores on all dimensions, which are concentrated in the urban core areas. Ordinary socio-economic status families provide a next best comprehensive score but weaker cultural dimensions of the family education environment, which are mainly distributed in the inner suburbs and the core of new urban areas. Low-income families provide an overall worse but better social dimension of the family education environment, which are mainly distributed at the edges of each urban circles. Low-education families provide the worst family education environment with the lowest comprehensive score, which are also mainly distributed in the outer part of each urban circles. 3) There are many factors in the family education environment that have an impact on the in-home learning experience. Among all the factors, the five dominant factors are: ‘Noise impact degree at home’ ‘Parental expectation’ ‘Study partner is your parent’ ‘Parents are able to help you solve problems of learning at home’ and ‘Number of extra-curricular books at home’, which reflect the importance of a quiet home environment, parental involvement, and a good family atmosphere for students learning at home. Urban circles had little effect on the in-home learning experience, and the dominant influencing factors were much the same across circles. The interaction of two factors significantly increased the explanatory power, indicating that in-home learning experience is influenced by a combination of factors.

The spatial spillover effect of urban factors plays an important role in the high-quality development of urban economy and regional coordinated development in China. Based on the rational construction of CD production function embedded in general nested spatial econometric model, this paper uses the data of 258 cities at prefecture level and above in China from 2000 to 2018 to measure the urban total factor productivity incorporating spatial spillover effect of factors to represent high-quality development of urban economy in China. At the same time, this paper uses appreciate production function embedded in general nested spatial econometric model to decompose the spatial spillover effect of capital and labour factors of specific cities and 5 major urban agglomerations, and explore the radiation driving capacity of specific cities and 5 major urban agglomerations to improve current situation of regional coordinated development in China. The results show that: 1) In terms of timing development, the overall urban total factor productivity in China has decreased slightly, but there is a gradual rising trend after 2017. In terms of spatial evolution, the total factor productivity in cities in southern and northern China has changed significantly, while the total factor productivity in eastern and western cities remains stable. 2) The result of measurement of urban total factor productivity with spatial spillover effect of factors is 0.4663 higher than that of those without spatial spillover effect of factors, indicating that spatial spillover effect of factors has a remarkable positive effect on urban total factor productivity. 3) Among the specific cities, the spatial spillover effect of factors of national central cities, and cities in the Bohai Bay, the Yangtze River Delta and the Pearl River Delta is strong, while the spatial spillover effect of factors of central and western cities is weak. Among the 5 major urban agglomerations, the spatial spillover effect of factors in Yangtze River Delta urban agglomeration is higher, while that in Chengdu-Chongqing urban agglomeration is lower.

Riparian dunes are ubiquitous in the main deserts all over the world, and their uniqueness is prominently reflected in the wind-water geomorphic process. In this study, the characteristics and variations of particle size and element composition were obtained through the analysis of the particle sizes and geochemical elements in the surface sediments from the Mu Bulag River located in the Hobq Desert. For characteristics of the particle size composition, the samples collected in 2013 and 2019 were extremely fine sand and dust sand, which accounted for more than 70% with narrow kurtosis and good sorting. These results of the sediments displayed typical aeolian characteristics. However, the samples collected in 2019 presented a coarser particle size and better sorting compared with that obtained in 2013. The Si and Al were the dominant elements for chemical composition in the sediments. Considering the average chemical composition of the upper continental crust (UCC), the loss of most chemical elements in 2019 were higher than with that in 2013. The A-CN-K diagrams revealed that the chemical weathering degree was low in the surface materials of riparian dunes in the basin, indicating a weak stage of removing Na and Ca, while other elements experienced unremarkable chemical weathering or migration. As for the samples from different river sections in both 2013 and 2019, the particle sizes belonged to finer with narrower kurtosis and better sorting, and thus the aeolian characteristics were more obvious from the upper to the middle and lower reaches of the river. Compared with the average chemical composition of the UCC, the consistency of element changes trends of samples in four sections in 2013 was more remarkable. For the basin scale, the physical and chemical characteristics of surface sediments of riparian dunes in different years showed great similarities, and these results can be attributed to the influences of parent rocks and the dynamic balance in surface materials under the alternate action of wind and water.

Chinese culture is centered on food. In the context of representation and non representation theory, food crosses communities, nations, and boundaries. The cognition of food comes from the mobile life practice. There are customarily such expressions as “the sweet flavor in the south, the salty flavor in the north” and “he rice in the south, the wheat in the north”, can this be seen as a metaphor for the existence of widespread food territorial stereotypes? Based on mobility, it is worth to explore whether the food regional stereotype evolves dynamically or statically. This study adopted a mixed approach to validate and measure food regional stereotypes. Applying the exploratory sequence design, this study consisted of three sub-studies. Study 1 used content analysis to initially examine the basic content of food regional stereotype. Data was crawled from Bilibili through Python, and used Rost CM6 software to analyze network text and construct semantic social network. Study 2 recruited subjects through convenience sampling and used the questionnaire survey to test the food regional stereotypes at the explicit level. Study 3 conducted Implicit Association Test to examine the existence of food implicit regional stereotype, and the experiment was designed with two within-subject variables (semantic consistency: consistency or inconsistency)×(objective area: south or north). Study 1 showed that the food regional stereotypes of the subjects were mainly reflected in the preferences of staple food and taste of the north and the south, which were specifically expressed as “sour in east, hot in west, sweet in south and salty in north”, consistent with the people’s previous cognition of food regional differences. Study 2 showed that the subjects tended to choose food words that matched the region, and formed eight specific dimensions, including: northern staple food, northern flavor, northern portion, northern dish, southern staple food, southern flavor, southern portion, and southern dish. Study 3 showed that: when the priming words of staple food, flavor, portion, and dishes were consistent with the target region (such as “noodles and the north”), the responding time was significantly lower than the inconsistency (such as “noodles and the south”). Overall, this study showed that the subjects held the regional stereotype of food in implicit and explicit levels, and the specific contents could be divided into four dimensions: staple food preference, flavor preference, portion preference and specific dishes. This study has the following implications. At the theoretical level, this stable place perception represented by food reflects the dialectical relationship between representation and non representation theory, and expands the research content of immobility under the new mobility paradigm. From the perspective of practice, this study tries to interpret commonsense food regional stereotypes in a scientific way, so as to improve the public’s understanding of food regional stereotype and reduce food cultural conflicts.

Since the Industrial Revolution, the agglomeration effect brought by the high specialization and division of labor of industry has continuously guided the concentration of elements and resources to cities. The rapid expansion has resulted in an increase in gathering costs, which has triggered a series of pressures on population, transportation, housing, environment, etc. These factors lead to the decline of the attractiveness of central cities and the transfer of urban development elements to multi centers. Among them, Shanghai has been exploring the breakthrough of polycentric development for a long time since the 1980s. The Shanghai Urban Master Plan (2017—2035) issued in 2017 proposed the new town development strategy of cultivating Shanghai’s Five New Towns into comprehensive nodes with radiating and driving capabilities in the Yangtze River Delta urban agglomeration. Therefore, based on the existing polycentric research and POI data, this paper studies the spatial structure characteristics of the Five New Towns in Shanghai during the polycentric process. Compared with previous studies on urban spatial structure, this paper focuses on the spatial distribution pattern of facilities at the micro level, at the same time, explores the combination characteristics of urban spatial structure between different circles, and innovates the research methods of urban spatial structure. Based on AutoNavi Maps point of interest (POI) data, this paper divides POI into 3 types of facilities: living, production and public. Kernel Density Estimation (KDE) and Ripley’s K Function are mainly used, and a triangular trajectory model is designed to reflect the structural evolution of facility types in space. Taking the main urban area of Shanghai as a reference, based on the number, distribution and aggregation degree of different types of facilities, this paper analyzes the spatial structure characteristics and distribution rules of facilities in the Five New Towns in Shanghai, and probes into the further construction direction of the five towns. The results show that compared with the urban area, the spatial distribution characteristics of facilities in the Five New Towns are significantly difference. The new towns with long development history have obvious single center spatial structure, while those with short development history show weak multi center structure. From the high-density circles to the low-density circles, the structure of facility types in the main urban area changes little, showing the characteristics of internal “convergence of urban functions”, while the Five New Towns show the trend of gradually decreasing the proportion of living facilities and increasing the proportion of public and production facilities. Between new towns, it shows the characteristics of “convergence of expansion structure”. In the high-density circles of the new towns, the proportion of living facilities is slightly higher than that of the main urban area, reflecting certain characteristics of “sleeping town”. In the low-density circles, although the proportion of production facilities is higher than that in the high-density circle, the concentration centers of 3 facilities are highly overlapped, indicating that the concentration center of production facilities is also in the central area of the new town, and its peripheral urban functions are weak, so there is no perfect “professional function center”. Therefore, the further construction of the Five New Towns needs to emphasize the balanced and coordinated development of facilities, improve urban functions and avoid the phenomena of “bedroom town” or “ghost town”.

Based on the data of the national censuses and 1% population sampling surveys from 1990 to 2020, this study investigates the characteristics and dynamic changes of the amount, source and destination selection of population outflow in the three northeastern provinces, namely Heilongjiang, Jilin, and Liaoning, from the perspective of structural and comparative analysis. The results show that population loss in the three northeastern provinces is a long-term phenomenon which could be dated back to the 1990s. However, the intensity of the population outflow in Northeast China is weaker than other regions with population loss such as central and western provinces according to the outflow amount and rate. The major cause of long-lasting population loss for Northeast China is not the huge amount of population outflow, but the combined effects of the low population inflow rate, the high outflow rate of registered residents, and the simultaneous outflow of urban and rural population. Compared with other provinces with population outflow such as Guizhou, Sichuan, Henan, and Anhui, the destinations of outflowed population from Northeast China are more diversified and decentralized. Economic factors are the common leading factors for the destination choice of the outflow population from Northeast China and other provinces. The outflow population from Northeast China prefer places that are geographically closer and have high-quality employment and public services, but no obvious evidence was found for their salient climate preference as previous studies claimed. The permanence and comprehensiveness of the lack of regional population attraction in Northeast China indicate that the regional governments not only should take measures to delay the outflow of population as much as possible, but also should actively explore new paths of high-quality development for better coping with population loss.

Plutonium (Pu) nuclide has strong radiation toxicity and biological toxicity, which is very harmful to animals, plants and human health. Thus, it is important to analyze the level, migration and pollution history of Pu isotopes in tree rings for ecological security and phytotoxicity evaluation. Under the background of the rapid development of China’s nuclear power industry along coastal areas, it is particularly necessary to establish the background data, including the Pu activity concentration as well as isotopic composition in the tree rings collected from different regions. In the present work, based on collecting and summarizing the limited existing literature and materials, the source and deposition mode of Pu isotope in the environment are briefly described. Then, the spatial pathway of Pu isotopes entering tree rings, the radial distribution characteristics of Pu isotope in tree ring samples as well as its environmental significance are also discussed. Finally, we emphasized the importance of developing chemical analysis method for accurately determining Pu isotopes with mass spectrometry technology and the research direction of its application research of this nuclide in tree rings, which is of great significance to promote the study of Pu isotopes as a tracer in the tree ring.

The urban thermal environment is deteriorating due to global warming and urbanization. Scholars worldwide are focused on lowering the land surface temperature (LST) to mitigate this issue. Building morphology significantly influences LST by affecting thermal radiation and wind speed. While numerous studies have examined the impact of 2D and 3D building morphologies on LST, many have lacked comprehensive consideration of relevant indicators and thorough analysis based on zoning schemes for various architectural features. In this study, the central urban area of Tianjin was used as a case study, and Landsat-8 remote sensing imagery was utilized to retrieve LST using the radiative transfer equation to characterize the urban thermal environment. Concurrently, building data were employed to quantify 17 building morphology indicators and identify 9 typical urban form prototypes. Subsequently, the differences in LST among the various urban form prototypes were analyzed, and the thermal environmental effects of building morphology within these prototypes were examined using multiple linear stepwise regression. The findings indicate that: 1) significant differences in summer LST were observed among different urban form prototypes, with the highest mean LST in low-rise, high-density blocks (42.58℃) and the lowest in high-rise, low-density blocks (38.16℃); 2) building morphology within different urban form prototypes had a significant impact on summer LST, although the degree of influence varied. The high-rise, high-density blocks had the greatest influence on LST (explanation degree of 45.9%), while the multi-rise, low-density blocks had the smallest influence (17.6%); 3) within typical urban form prototypes, there was a coexistence of differences and consistency in the response of summer LST to various building morphology indicators. Across all urban form prototypes, the direction of influence of each building morphology factor on LST was consistent, but its relative importance varied. Therefore, future urban planning and urban renewal should avoid low-rise, high-density configurations and prioritize high-rise, low-density ones to enhance the thermal environment. Adjusting and regulating building morphology within limited land and space resources can improve the urban thermal environment. Differentiated building morphology planning and design strategies should be implemented with targeted solutions based on the thermal effects of various urban form prototypes.

At 23:59 on December 18, 2023, an earthquake with a magnitude of M_S 6.2 occurred in Jishishan County, Gansu Province, and at the same time a mudflow secondary geologic disaster broke out in Qijiagou, Zhongchuan Township, Minhe County, Qinghai Province, which is a typical secondary geological disaster of the same earthquake and transformed into a disaster by the coupling and superposition of multiple disasters such as earthquake, landslide and mudflow, and its impact and effect are much greater than that of a single disaster. Through all kinds of methods such as field survey and measurement, remote sensing image analysis, empirical formula estimation and villagers’ interviews so as to recover and reappear the chain process consisting of “agricultural irrigation-static liquefaction-local plastic deformation-potential slip formation” and “earthquake-dynamic liquefaction-seismic slip through-slump slip-mudflow”. This article discusses the geomorphological characteristics and occurrence process of mudflow in Qijiagou, and conducts a preliminary discussion on its causes. The results showed that: 1) The Qijiagou mudflow, with a total length of about 3.0 km and a disaster-forming area of about 0.478 km², there are all kinds of types of landforms, so it is a typical mudflow-hazard geomorphologic process with a full range of geomorphologic types. 2) the instantaneous maximum flow rate of the first wave of viscous mudflow in Qijiagou was above 10 m/s, and the mudflow head reaches Caotan Village in Zhongchuan Township almost at the same time as the earthquake, and the subsequent intermittent mudflow velocity was about 7.1, 6.0 and 5.8 m/s, compared with the mudflow head, it’s twice as small and gradually decreased; 3) Irrigation over a long period of time, leakage of water channels and pre-earthquake winter irrigation led to the pre-saturation of loess layer in mudflow formation area, and seismic oscillation load causes the liquefaction of underground saturated loess layer, earthquake triggered a sudden increase of excess pore water, the mudflow high speed, low slope drag reduction movement pressure may be the key mechanism for the formation of high-speed mudflow. 4) Winter irrigation on agricultural land and failure to close the electric switch in time after earthquake were the main hydrodynamic conditions of subsequent intermittent mudflow, as well as the human factors that led to mudflow disasters. The co-seismic mudflow is formed by the coupling of multiple factors so it’s very special for research, we should increase our efforts to protect this rare geological site. It is recommended to be protected as geological disaster relics, we should carry out protection zoning, and strengthen the assessment of geologic disaster risk of water conservancy projects in the Yellow River plateau irrigation area, pay attention to preventing the occurrence of loess landslides.

Understanding the relationship between climate change and the lake ecosystem variations is crucial for studying the impact of global warming on the lake carbon cycling process. However, less is known of how lake ecosystem variations responding to the global warming in different lakes on the Qinghai-Xizang Plateau (TP) where thousands of lakes distributed. Here we present comparison researches from Aweng Co (81°37′48″E~81°48′00″E, 32°42′00″N~32°48′36″N, 4430 m a.s.l.) and Toson Lake (96°50′00″E~97°03′00″E, 37°04′00″N~37°13′00″N, 2808 m), they are closed lakes with different hydrological process. Aweng Co (pH is 9.2, salinity is 29.5 g/L) is mainly supplied by glacier melt water via groundwater and precipitation. And Toson Lake (pH is 8.4, salinity is 35.7 g/L) is at the end of Bayin River drainage basin, and it is fed by precipitation and the flowing from Herleg Lake. There are villages and farmland in the upstream of the Toson Lake. Two sediment cores were drilled from the lake center in Aweng Co and Toson Lake, they were AWC2015 (445 cm) and TSL17G (55 cm), respectively. The top sediment of AWC2015 and TSL17G were measured by ²¹⁰Pb and ¹³⁷Cs. We focused on the lake carbon cycling process in the two lakes in recent 100 years. Multi-proxy including organic carbon isotope, total organic carbon content and organic carbon accumulation rate were measured to reconstruct the lake productivities and carbon burial rates in two lakes. Results showed that global warming had different impacts on the photosynthetic process in different lakes depending on the lake level, actual temperature and sunlight at the lake bottom. In Aweng Co, when the values of δ¹⁸O_carb tended to be negative, and TOC content increased, indicating that more glacier melt water supplied the lake, resulting in expanding of the lake area, more nutrient supplying the lake, and improving of the lake productivity consequently. However, when plenty of glacier melt water flowed into the lake in short time and the water temperature decreased rapidly, slowing down the photosynthetic process and resulting in decreased carbon burial rate consequently. In the human-disturbed lake, the variations of δ¹⁸O_carb and TOC content indicated that human activity played more important roles in driving aquatic biomass by influencing sunlight at the lake bottom via lake level change. With the increasing of water consumption for agriculture, the water that finally supplied the lake would decrease, and resulted in lower lake level and more light reaching the lake bottom, favoring the growth of the benthic algae, and the organic carbon burial rate increased finally, and vice versa. Therefore, global warming had different impacts on the carbon cycling process in lakes with different hydrological process.

This article takes six batches of 8171 Chinese traditional villages as the research object, and uses spatial analysis method to explore the spatial distribution characteristics and influencing factors of traditional villages based on geographic grid. The main conclusions were as follows. Firstly, the spatial distribution pattern of traditional villages is characterized by a significant inter provincial boundary phenomenon of concentrated traditional villages, with three major agglomeration areas. The border between Hebei, Shandong and Henan province, the border between Anhui, Zhejiang and Jiangxi province, and the border between Guizhou, Guangxi and Hunan province. Secondly, the spatial autocorrelation of traditional village spatial distribution is obvious, with “high and high” “low and high”, and “low and low” spatial clustering. The mountainous and hilly areas south of the Yangtze River are the dense areas of traditional village distribution in China, while the northeast and northwest border areas are the sparse areas of traditional village distribution. Thirdly, the impact of transportation and economic factors on the spatial distribution of traditional villages is not significant. The factors of terrain, temperature, ecology, and population have a positive impact on the spatial distribution of traditional villages, while precipitation factors have a small negative impact on the spatial distribution of traditional villages. The impact of population, town, and ecology factors on the spatial distribution of traditional villages has strong spatial heterogeneity. The research results have deepened two important understandings about the spatial distribution of traditional villages. One important understanding is that the phenomenon of inter provincial boundaries in the dense distribution of traditional villages is significant. These regions have similar geographical environmental characteristics, mainly consisting of mountainous and hilly landforms, with the environmental characteristics of “three lows and one excess” (low annual temperature, low road density, low economic development level, and high annual precipitation), which fully indicates that the natural geographical environment has a very important impact on the formation and protection of traditional villages. Another important understanding is that the factors that affect the spatial distribution of traditional villages have spatial heterogeneity. It can be seen that the factors with strong heterogeneity are mostly socio-economic factors. This conclusion provides useful insights for subsequent research on the spatial distribution and influencing factors of traditional villages. Compared with existing research literature, the contribution of this article lies in achieving the cross fusion of traditional village spatial location with multi-source data such as natural geographical factors and socio-economic factors, further verifying the effectiveness and scientificity of spatial regression models in analyzing the influencing factors of point vector elements, and enriching the technical methods for studying the spatial distribution and influencing factors of point vector elements.