Environmental economic geography emerges as a reflection of the marginalization of the environment within the discipline of economic geography. It seeks to re-establish the linkage between economic geography and the environment. After almost two decades of development, environmental economic geography is still suffering from its poly-vocal, fragmented, and marginalized issues. This study scrutinizes the debates over the research agenda on environmental economic geography and reviews two primary strands of the literature. On this basis, this study discusses challenges for the future development of environmental economic geography. This study comes to four conclusions. Firstly, the development of environmental economic geography follows the theoretical advances in economic geography. It explore how environmental changes modify the spatial patterns of economic development. It also investigate how the spatial configuration of economic activities responds to the rising environmental risks and intensifying resource scarcity. Two research themes emerge, namely environmental governance and green transition. Secondly, environmental economic geography uses the theoretical framework of the Global Value Chain (GVC) and Global Production Network (GPN) to investigate how firms and regions can simultaneously upgrade in environmental and economic terms. It also seeks to establish the linkages between GVC/GPN governance and environmental governance. On the other hand, environmental economic geography identifies environmental regulation as a locational factor and examines its role in the location choice model. The empirical result offers various counter-examples for classical hypotheses, such as the Pollution Haven Hypothesis, the Porter Hypothesis, and the Environmental Kuznets Curve Hypothesis. Thirdly, environmental economic geography combines its theoretical interests with the theoretical advances in evolutionary economic geography. Particularly, the regional diversification theory and the path creation theory are incorporated into the empirical studies of environmental economic geography, which seek to unravel the conditions and processes of green transitions. Based on these theories, recent studies also offer some predictors for the regional green transition. Lastly, this study proposes that environmental economic geography is still suffering from the divergence between natural science and social science on research paradigm. Besides, the theoretical development of environmental economic geography is subject to a late-comer disadvantage. In this regard, it requires environmental economic geography to become more problem-oriented in the future, embracing the opportunities embedded in the issues for China’s sustainable development.

In recent years, the concept of sustainability transitions and its related research have increasingly drawn attention from economic geographers. Sustainability transitions studies aim to investigate the multi-scalar causality of mechanisms and spatial dynamics on how regional green technologies, consuming markets and industrial transformations emerge and develop over time. This research strand has become one of the emerging topics in both evolutionary economic geography and environmental economic geography. To better capture the progress of sustainability transitions studies, this paper conducts a bibliometrics-based literature review based on 2453 articles in the field during the past two decades. Besides, through an in-depth critical review on geographies of transitions, this paper identifies several key theoretical problems and shortcomings in the geographies of transitions literature. It has addressed the theoretical merits and value of economic geography for improving sustainability transitions studies. The findings of the paper are: (1) As one of the most promising research themes in innovation studies, sustainability management and environment science, sustainability transition studies have been increasingly disciplinarily pluralistic. The economic geographical research on sustainability transitions, in particular, focuses on three key research topics, including the co-evolution mechanisms between technologies and societies in regional new green industrial path development, multi-scalar driving forces and agency-structure interactive mechanisms of sustainability transitions, the role of transitions in shaping environmental economic and socio-spatial impacts, and the varieties of transition mechanisms. (2) There are in general three perspective advantages of economic geography for transitions studies that can be identified, namely, spatio-temporal sensitivity, spatial varieties of transition mechanisms, processes and impacts/outcomes, and place embeddedness of new socio-technical regimes in industrial systems and its geographies of legitimation. (3) Three orientations for economic geography to enhancing transitions studies are identified: deepening of geographical concepts (including place, scale and space), interactions and integrations with different approaches in economic geography (namely, transitions with evolutionary, institutional, and geographical political economy), and construction avenues for comprehensive analytical frameworks (integration of geographically multi-scalar perspective with multi-level perspectives, and that of regional innovation systems perspective with the approach of technological innovation systems. (4) Three promising research agendas on geographies of transitions in China are proposed, namely, localized transitions research by incorporating the role of Chinese-specific national contexts, green niche development and spatial mechanisms of its transitions, and regional new industrial path development and its related transition studies.

The research on location and relocation of polluting enterprises, including their associated mechanisms, is a hot topic in environmental economic geography, which has attracted extensive attention of scholars and policy makers. Existing studies have explored the influencing factors of local government environmental regulations on the entry and exit, spatial distribution and industrial transfer of polluting enterprises from the perspective of formal institutions, while relatively ignoring the role of informal institutional factors such as local social capital, residents’ environmental awareness and corporate environmental responsibility which also has a potential impact on enterprise exit. Based on the Chinese industrial enterprises data in 2011, China General Social Survey (CGSS) data and urban statistical yearbook data, this paper constructs China’s urban scale social capital from three aspects of social norms, social networks and social trust, and uses the binary logit regression model to explore the impact of social capital and environmental regulation on the exit of Chinese polluting enterprises. The results show that:(1) The role of environmental regulation has been verified with a threshold effect in the promotion of environmental regulation on the exit of polluting enterprises. (2) Social normative factors, such as public environmental awareness and corporate environmental responsibility, constitute external informal environmental pressure on the survival of polluting enterprises and positively support the exit of polluting enterprises; However, social trust and social network have no direct and significant effect on polluting enterprises as expected. (3) Interactive model shows that social capital has a positive interaction with environmental regulation in area with high environmental regulation, which can form a positive relation between formal and informal systems. Such relation constitutes a strong driving force for polluting enterprises withdraw from the local market. This study suggests that informal institutional environment has an important impact on the survival of polluting enterprises and there are rich interactive activities with environmental regulation. The present study explains influence mechanism of polluting enterprises exit from the perspective of social capital, which complements the existing research on environmental regulation from the informal institutional aspect. Meanwhile, it provides a practical reference for the sustainable operation of polluting enterprises and the formulation of environmental governance policies.

Environmental justice studies focus on the spatial justice of people's life quality. With the rapid development of urbanization and industrialization, industrial pollution has led to intensifying environmental degradation. Due to the spatial distribution of polluting enterprises, the levels of environmental degradation vary among urban settlements in the city. Recently, this variance has become a major environmental justice concern in China. Based on this understanding, it is imperative to understand the relationship between distribution of polluting enterprises and the social characteristics of the regional population from the spatial and temporal perspective. Cities with many industrial enterprises can lead to differential distributions in residential settlements. Guangzhou, a typical city, is selected as the empirical case. Based on a collection of enterprise census of 1995, 2004 and 2013 and the population census data of 1990, 2000 and 2010, this study analyzed the distribution of polluting enterprises and its spatial changes using ArcGIS visualization tool, and further examined the spatio-temporal changes of relationship between polluting enterprises and sociodemographic characteristics of regional population in Guangzhou by geographic weighted regression model. We find that the clustering of polluting enterprises has transferred from the central city to the suburban and border areas. The regression results reveal that old people and immigrants had become the main groups greatly affected by enterprise pollution in the 1990s, whereas differences among social classes including social stability, educational level and income level are related to the spatial distribution of polluting enterprises since 2000. This change of spatial relationship reflects the reconfiguration of urban industries and socio-spatial differentiation in modern Guangzhou. Further analysis discovers that the spatially influenced environmental injustice of pollution evolves from insignificance to a significantly city-wide relationship between different social classes and the pollution burden of enterprises. This evolution is different from the characteristics and mechanisms in a Western context. Compared to their Western counterparts, the public environmental resources are endowed with commodity attributes and the fundamental driving force to redistribute spatial environmental benefits through profit capture under the Chinese social market system. Based on our findings, this research further calls attention to seriously considering the environmental rights of low-income classes and emphasizing the need of public participation when making relevant policies.

Facing the severe problem of agricultural non-point source pollution, the diffusion and adoption of environmentally-friendly agricultural technology is of decisive significance to the modernization and the revitalization of ecology in rural China. However, environmentally-friendly agricultural technology is currently hard to promote and with a low acceptance in rural areas. Previous studies have proved that social network is an effective way and foundation for technology diffusion. Correspondingly, this paper constructs a theoretical framework of environmentally-friendly agricultural technology innovation diffusion from the perspective of social networks. Through the quantitative analysis of questionnaire data of 3015 households in 10 counties and cities of Guangdong Province from 2018 to 2020 and the fieldwork observation of non-point source agricultural pollution control in this province, this paper concludes that there are four stages of environment-friendly agricultural technology diffusion: (1) Initial stage: discrete and simple technical interaction among rural households emerges. (2) Single-core stage: single core such as elite farmer has formed and technology starts to diffuse through kinship network. (3) Multi-core stage: there have been several elite farmers and the diffusion goes through occupational network rather than kinship. (4) High-level interaction stage: agricultural economic organization and agricultural entrepreneur have been established; functional network has been formed. Behind the four stages, individual farmers keep on accumulating their own material, human and social capital to achieve the upgrade of their node level, also known as the process of technology diffusion, from disorder to formalization. Correspondingly, there are four main influencing factors of the diffusion of environmentally-friendly agricultural technology: individual resource endowment, technology effectiveness and perception, technology diffusion channels and external environment. These factors play different roles in different stages. The results of this study can be beneficial to the understanding of the underlying mechanism of environmentally-friendly agricultural technology diffusion in rural China, and are of policy significance for the diffusion and adoption of similar technologies. According to the stage characteristics of the diffusion of new technology, the government needs to guide and promote the mode of communication in accordance with local conditions.

As an essential loop in China′s low-carbon transition progresses, energy-intensive industries played irreplaceable roles in achieving carbon peak and carbon neutral goals. Based on the industrial upstream and downstream linkages, this study attempts to compare the changes between the production- and consumption-based carbon emissions, construct China's embodied carbon emission networks through industrial linkages, measure the embodied carbon transfer efficiency between upstream and downstream industries, trace the carbon risk transmission of energy-intensive industries, and identify the key nodes and paths under low-carbon transition. The main conclusions are as follows:(1) There remains a huge gap between the production- and consumption-based carbon emissions. The direct carbon emissions of energy-intensive industries accounted for about 80% in China's overall industrial system, while the corresponding consumption-based carbon emissions accounted for less than 10%. (2) The embodied carbon transfer efficiencies of petroleum processing, chemical raw materials and products, non-ferrous metal processing industries′ upstream and downstream are relatively high, while the embodied carbon transfer efficiencies of the electricity production and supply, non-metallic mineral products, and ferrous metal processing industries' upstream and downstream are relatively low. (3) Along with the increase of the industrial linkages, the proportion of energy intensive industries' embodied carbon emissions decreased by the production layer, and the key nodes and paths in carbon risk transmission of energy-intensive industries are different. (4) The carbon emission reduction per unit of value added in energy-intensive industries including electricity production and supply, ferrous metal processing, and non-metallic mineral products were higher than that of other energy-intensive industries, with relatively high carbon emission reduction efficiencies and more significant carbon emission reduction efficiencies. Through constructing the embodied carbon emission networks through industrial linkages and identifying the key nodes and paths of carbon risk transmission under low-carbon transition, this study is expected to provide practical quantified supports and policy implications for the sustainable low-carbon transition and potential risk prediction related to China's energy-intensive industries.

E-commerce and other new forms of consumption have developed rapidly in recent years, and their impact on carbon emissions can not be ignored. In terms of the spatial decomposition and the embodied carbon transfer, based on the research of the carbon footprint in the e-commerce express box life cycle, we study the geographic spatial couplings between the e-commerce behavior and carbon footprint in the raw material production, manufacture and consumption stages, and analyse the pattern characteristics of the emissions by stage and aggregate at provincial level, and the network layout of the embodied carbon emission transfer with the express flow. The results show that the carbon emissions in the raw material stage are mostly in the location of wood raw material suppliers, while the carbon emissions in the production stage are highly coupled with the location of express delivery, and the carbon emissions in the utilization stage are coupled with the location of express receiving area. The carbon emissions of e-commerce express box cartons in China of every stage are highly concentrated. The carbon emissions in the raw material stage are mainly concentrated in Guangxi, while in the production and consumption stages are concentrated in Guangdong, Zhejiang and Jiangsu, showing a general distribution pattern of "more in the eastern region and less in the western region; more in the southern region and less in the northern region". Provinces with higher total carbon emissions are mostly driven by production, while provinces with lower total carbon emissions are mostly driven by consumption. The embodied carbon emission transfer network presents a "hub-and-spoke" structure of "net outflow in few provinces, while net inflow in most provinces". Zhejiang and Guangdong, accounting for about 80% of the net outflow, are the largest places of departure of the embodied carbon emission inflow of most provinces, while Beijing is the sample with the largest net inflow. The division of responsibilities based on the embodied carbon emission transfer is an important factor of management decision, while the green packaging has made a great contribution to emission reduction, so it is urgent to seek technological breakthrough, and the carbon emissions of new consumption forms deserve long-term attention.

Global warming is a great challenge faced by all mankind. The continued increase in greenhouse gas emissions will have a negative impact on agricultural production, socio-economic activities and human life, and ultimately hinder the process of achieving global sustainable development. This study attempts to introduce the variable of digital economy development into the research framework of carbon emission impact factor theory to systematically examine the effect of digital economy development on urban carbon emissions. This study was conducted to investigate the spatial effects of the digital economy on urban carbon emissions. Based on the panel data of 286 cities from 2011 to 2017, this study analyzes the impact of digital economy development on urban carbon emissions using the spatial Durbin model and the spatial DID model. The main conclusions are as follows:(1) There is spatial heterogeneity in the development pattern of digital economy, and the development pattern changes from "multi-point" sporadic distribution to "cluster" agglomeration, but the gap between the development levels of cities has not been narrowed, and the Yangtze River Delta becomes an important digital economy agglomeration area. (2) The digital economy has a significant negative effect on urban carbon emissions, and the findings are robust to the introduction of the exogenous policy shock of "smart cities". Moreover, there is spatial heterogeneity in this effect, with the negative effect of digital economy on carbon emissions being stronger in the eastern region, and the influence of digital economy is stronger in regions located within urban agglomerations. (3) In order to investigate the spatial decay characteristics of the spillover effect of the digital economy on urban carbon emissions, the spillover effect analysis of the multi-distance economic circle is carried out, and it is found that the spillover effect of the digital economy on carbon emissions peaks at 1100 km. (4) The coverage of digital infrastructure does not have a significant negative effect on carbon emissions in the region, while digital industry development, digital innovation capacity and digital inclusive finance all have a significant negative effect on carbon emissions in the region and neighboring areas. This study adds to the lack of research on the digital economy and carbon emissions, and provides some theoretical reference for the study of the environmental improvement effects of the digital economy.

Based on the number of patent applications in the field of solar and wind energy submitted in 367 cities in China, we measure the technological innovation ability of China's new energy industry. Then this industry’s innovation phases, spatial distributions, spatial correlations and influencing factors between 2001 and 2018 are explored by means of Gini coefficient, spatial autocorrelation and spatial measurement model. Results show that: (1) The technology innovation and development in China's new energy industry presents an overall growing trend, with obvious phase characteristics and different changing trends. Oil crisis and financial crisis are two important events in the development process, where national incentive policies also play an important role. (2) The Gini Index of the eastern region where innovation outputs are mainly concentrated shows little change; in contrast, the Gini Index of the central and northeastern regions shows a decline trend. On the other hand, the innovation ability is weak in the western region, with the largest difference in innovation ability related to new energy technologies. (3) High level innovation hotspots are widely distributed across developed cities. (4) The Moran's I value for technological innovation capabilities in solar and wind energy is both positive and rising, indicating that there is a significant spatial correlation in terms of new energy technological innovation capabilities in cities, and the spatial agglomeration gradually intensifies. The H-H cluster areas are mainly distributed in the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region, while the H-L cluster areas are mainly distributed in the provincial capitals of central and western regions, with no obvious driving effect for neighboring cities, or with only limited radiation effect. (5) Economic foundation, education level, industrialization level, electricity demand, human capital, technology investment level, environmental regulation, resource endowment and urban innovation ability all have some impact on the development of the new energy industry’s technological innovation of cities. According to the four major regional factors, the influence and constraints of the development in solar and wind energy technology innovation have obvious regional heterogeneity. The level of economic development is the primary driving factor and an important foundation for bolstering the technological innovation and development of the new energy industry. The regional effects of environmental regulations, industrial structures and resource endowments are significantly different.

The carbon neutrality target is not only China′ s commitment to climate governance, but also the endogenous demand for high-quality economic development. This paper, based on China′s energy consumption, land utilization pattern and input-output data, is aimed to conduct research on China's inter-provincial ecological security, coordinated development and carbon ecological compensation in the context of basic theoretical framework of ecological footprint. The conclusions of this paper are as follows. (1) Ecological security and regional coordination level continue to decline, which present the characteristics of regional convergence. From 2000 to 2017, the ESI index of China as a whole rose from 1.08 to 3.06, and the ECI index decreased from 1.413 to 1.261. The level of ecological security and coordinated development in 24 provincial-level regions declined. The level of ecological security and coordinated development showed an obvious trend of consistency, i.e., low coordinated development level in regions with low security level, and high coordinated development level in regions with high security level. (2) China is witnessing rapidly growing ecological "debt". Regional ecological compensation shows the following characteristics:eastern China "pays compensation", western China "accepts compensation", and central China "maintains a balance". Based on different policy objectives, this paper designs two ecological compensation schemes:"net zero emission" and "net zero contribution". Under the "net zero emissions" scheme, China's ecological compensation payments increased from $1334.57 million to $83819.61 million during the study period, a 60-fold increase over 17 years. On the regional compensation structure, the three coastal economic zones are long-term compensation payment areas, but the proportion of compensation payment in the whole country is gradually declining; correspondingly, the proportion of compensation payment in the middle reaches of the Yellow River and the middle reaches of the Yangtze River increased rapidly. Under the net zero contribution compensation scheme, China-wide compensation achieves accounting balance. Regionally, eastern China pays for carbon offsetting, western China is compensated, and central China can basically keep the balance.

Based on the data of 61 prefecture-level cities in the Yellow River Basin from 2005 to 2017, this paper constructed the input-output index system of green development efficiency, and used various spatial econometric models to examine the spatio-temporal pattern characteristics and influencing factors of green development efficiency in the study area. The following conclusions can be drawn as follows. (1) The regional differences of green development efficiency are gradually widening, evolving from “small differences and high efficiency” to “large differences and low efficiency” totally, which indicates that the club convergence characteristics of green development efficiency are obvious. (2) Scale efficiency makes significant contribution to the growth of green development efficiency, showing that large-scale agglomeration and intensive development are still an important guarantee for the improvement of green development efficiency. However, science and technology have not yet played an important driving role in improving the green development efficiency. In the future, improving the level of science and technology in this basin is the key to optimizing and improving the green development efficiency. (3) There is an obvious spatial reliable correlation of green development efficiency within the study period, and the regional spatial agglomeration featured with similar green development efficiency level is significant. (4) The spatial distributions of green development efficiency are obviously diverse, and the regional differences between the east-west distribution and north-south distribution of high-efficiency areas are prominent, which mainly shows a cluster development stimulated with urban agglomeration. and reflects that the green development efficiency of the study basin has a circular cumulative path dependent effect. The influencing factors of green development efficiency in the Yellow River Basin can be attributed to the adjustment effect of industrial structure, the growth effect of economic development, the demonstration effect and spillover effect of science and technology, the government regulation mechanism and market-oriented mechanism. Finally, Tobit regression model is used to analyze the influencing intensity and direction of industrial structure, economic development, science and technology, government regulation and marketization level on green development efficiency in the Yellow River Basin and its subzones.

The Yangtze River Delta is a demonstration area for China's high-quality integrated development and an important area for China to achieve its peak dioxide emissions by 2030 and carbon neutrality targets by 2060. In the context of the transformation of China's administrative region economy to an integrated economy, the regional integration of the Yangtze River Delta has reduced administrative barriers and optimized the allocation of factors. At the same time, what impact does it have on urban carbon emissions? Based on the panel data of prefecture level and above cities in China, this paper regards the issuance of The Regional Planning of Yangtze River Delta as a quasi-natural experiment, using the difference-in-difference (DID) method to estimate the effects of regional integration in the study area on urban carbon emissions. Furthermore, by using the mediation effect model, we identify the possible internal mechanism of regional integration on carbon emission effects. The results showed that regional integration policy of this delta in 2010 significantly reduced urban carbon emissions, and after a series of robustness tests such as the parallel trend test, PSM-DID and placebo test were still true. From the perspective of dynamic effects, the carbon emission reduction effect appeared in the third year after the issuance of regional integration policy. At the same time, compared with general hierarchy cities, regional integration had a greater effect on carbon emissions reduction of high hierarchy cities. Mechanism verification showed that regional integration policy aggravated urban carbon emissions through the strengthening of economic links between cities, and reduced urban carbon emissions by promoting the upgrading of the industrial structure and the improvement of urban technology. From the perspective of better achieving the goal of high-quality integration in the Yangtze River Delta, it is suggested that the delta should actively explore the cooperation mechanism of carbon emission reduction and green development between cities, and establish a green development evaluation index system that can be monitored and operated. Besides, we should focus on the green transformation of industries and increase investment in green technology research and development among cities in the Yangtze River Delta.

The manufacturing industry consists of many polluting sectors. The unreasonable spatial pattern of the manufacturing industry causes environmental problems, especially PM_2.5 air pollution. Northeast China is a typical old industrial base. Many of the problems facing its manufacturing industry, such as the heavy and single industrial structure and unreasonable industrial layout, need to be addressed urgently. In the new period of the construction of a national ecological civilization and overall revitalization of Northeast China, research into the evolution of the spatial pattern of manufacturing industry and its environmental impacts on air pollution is of great importance for optimizing regional industrial spatial layout, advancing industrial transformation and upgrading, and promoting coordinated economic development. This paper analyzes the spatial pattern and environmental impacts of the manufacturing industry in Northeast China in the period 2005-2020, using a large dataset with 43112 data records on above-scale enterprises. Multiple spatial data analysis techniques, such as kernel density estimation, nearest neighbor analysis, spatial autocorrelation analysis, and spatial lag model were used. The results show that: (1) In Northeast China, the agglomeration hotspots of manufacturing enterprises are mainly located in the ‘Harbin-Changchun-Shenyang-Anshan-Dalian’ axis area, and the overall level of the agglomeration is gradually increasing. Among them, the agglomeration level of high-tech industries is higher, while that of low-tech industries is lower. The capital scale has expanded from a high degree of concentration to cities along the ‘T’-shaped railway. (2) The industrial structure cleanliness and the industrial technology upgrade are gradually declining. The two indices are spatially different at the county scale and have different magnitudes of increase and decrease. High-polluting enterprises are mainly located in the central and southern parts of the region. (3) The spatial pattern of the manufacturing industry has significant agglomeration and technical effect on air pollution, but the scale and structural effect are not significant. With the increasing number of manufacturing enterprises and the increasing degree of specialization of high-tech industries, the effect of congestion and the effect of rebound are formed, respectively, and both will aggrevate local air pollution. In addition, population density exacerbates regional air pollution.

Resource and environmental constraints pose severe challenges to China's energy consumption. Smog can be seen as a concentrated outbreak of long-term accumulation of structural contradictions in terminal energy consumption. With the help of K-means clustering, spatial correlation analysis and other methods, this paper systematically studies the spatiotemporal characteristics and structural evolution of the terminal energy consumption of 30 provincial-level units. Furthermore, the spatial measurement model is used to explore the impact of terminal energy consumption on environmental pollution from multiple perspectives. The results show that: (1) Per capita terminal energy consumption of each provincial-level unit has increased to varying degrees during the study period, but the inter-provincial differences are still significant. (2) In terms of terminal energy consumption, during the study period there is a significant positive spatial correlation, indicating the existence of spatial agglomeration characteristics, and the formation of a variety of spatial agglomeration types. (3) As for terminal energy consumption structure, due to large differences in resource endowments and industrial structures, various types in different provincial-level units show diversified evolutionary characteristics. (4) Through spatial econometric model testing, it is found that terminal energy consumption has a significant positive impact on the air quality index, and this impact differs in different energy consumption types. There are obvious differences between the structure and different regions. (5) Based on the research conclusions, targeted countermeasures and suggestions for energy consumption and structural optimization are put forward, in order to provide ideas and references for reducing carbon emissions and improving air quality. Finally, this article attempts to explain the impact of energy on air pollution from the consumption side of energy, but the production side of energy and the intermediate stage of processing and conversion may also form a more complex path of impact on environmental pollution, which is worthy of further analysis. In addition, with the continuous advancement of environmental protection technology, China's clean energy continues to increase, gradually transforming from auxiliary energy to main energy, and a clean, low-carbon, safe and efficient energy system is being built. Therefore, the complex relationship between clean energy production, consumption, resource allocation, technological innovation, and market-oriented reforms, and air quality will become the focus of subsequent exploration.

As the economic development entered the transitional stage, the limitation and drawbacks of the traditional extensive growth model of land-based development has become more obvious, which not only causes excessive consumption of resources, but also leads to prominent environmental problems. Urban development is facing pressures from economic growth and environmental protection. In China, it is worthy to study what action strategy the local governments will implement when facing this dilemma as the agent of the central government. It has been found that local governments often transfer industrial land with large area and low land price to promote local economic development. However, there have been fewer studies on the regional environmental influences and effects caused by industrial land transfer. Whether the local government has considered the resource and environmental constraints in the process of industrial land transfer? What are the characteristics of its current industrial land transfer behavior? What are the environmental effects and what is the internal mechanism? To answer these questions, this study develops a variable lag panel data regression model using 284 cities data from 2015 to 2019, in which the independent variable is the urban annual air quality index (AQI), and the core explanatory variable is the transfer area of different types of industrial land. The conclusions are as follows. (1) First, the expansion of industrial land will significantly exacerbate urban air quality, and the influence has spatial heterogeneity. (2) The way of industrial land transfer has a significant impact on the urban environmental quality. The environmental pollution of industrial land transferred by agreement is greater than that of industrial land transferred by bidding, auction and listing. The larger the scale of land transferred by agreement, the worse the urban air quality would be. (3) The choice of industry is an internal mechanism on how the transfer of industrial land affects quality urban air. Local governments prefer to supply lands for pollution-intensive industry by agreement, which results in exacerbated environmental quality. This is different from the standpoint holding that industry projects are always of poor quality thus aggravating environmental quality. The study indicates how the local governments’ land supply behavior affects urban air quality from the perspective of industrial selection mechanism, thus expanding the existing literature and providing policy references for urban ecological civilization construction.

There is always a debate about the relationship between foreign direct investment and its domestic environmental outcome. The Pollution Haven Hypothesis argues that multinational firms in developed countries will relocate their dirty production to some developing countries to seek low compliance costs but the Pollution Halo Hypothesis emphasizes that multinational firms transfer their green knowledge and practice to the host country bringing favorable environmental benefits to domestic firms. This paper aims to examine the environmental spillover effects of foreign firms on domestic firms. Specifically, this paper compares the emissions intensity of SO₂ (sulfur dioxide) and COD (Chemical Oxygen Demand) between foreign and domestic firms and their spatiotemporal evolution using matching data of pollution emissions and production from industrial firms in China between 1999 and 2012, and then, uses an econometric model to identify the environmental spillover effects of geographic agglomeration of foreign firms. The results show that: (1) during the study period, the total emissions of SO₂ and COD of Chinese industrial firms showed a gradual decline, mainly due to the reduction of the total emissions of domestic firms, while the total emissions of foreign firms did not change significantly. (2) During the study period, the SO₂ and COD emission intensity of domestic firms decreased rapidly and gradually caught up with that of foreign firms. Domestic firms with low emission intensity in China are mainly located in the coastal areas with a relatively high level of economic development; meanwhile the emission intensity of inland areas has experienced a rapid decline. (3) Empirically, for both within and between industries, the geographical agglomeration of foreign firms can significantly reduce the emission intensity of domestic firms, but the effect and significance of intra-industry spillovers are higher than that of inter-industry. The environmental spillovers of foreign firms can affect domestic firms through three channels: labor mobility, competition effect and the embedding effect of local production network. In terms of the embedding of local production network, empirical evidence shows that the backward link can show environmental spillover effects, while the forward link effect is not significant. In the heterogeneity analysis, compared with high-efficiency firms, low-efficiency firms can benefit from environmental spillover effects by labor mobility or embedding in foreign production network, but cannot obtain environmental spillovers from the competitive effects.

Under the background of globalization, rapid urbanization and new technological revolution, the "flow space" composed of factor flow and network relationship was becoming more and more important, the city network structure was constantly impacted and reshaped, the contradiction of man-land relations was becoming increasingly prominent, the regional spatial organization patterns and its environmental effect have become an important topic of environmental economic geography research. In this paper, we used Tencent location big data to establish population migration network among 288 China's cities above prefecture level from 2015 to 2018, and employed social network analysis and panel spatial econometric model to empirically analyze the evolution patterns of city network and its environmental effects in China. The results show that: (1) Cities with high connection strength in China's city network are mainly distributed in the rhombus structure consisting of the Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, and Chengdu-Chongqing urban agglomerations in the region east of the Hu Huanyong Line. China's city network density and relevance were gradually increasing, and degree centrality and betweenness centrality presented a trend of multi-center and decentralization. (2) On the whole, China's urban air quality has improved, showing significant agglomeration characteristics in space. Ambient Air Quality Index (AQI) decreased in 256 cities (88.89% of the country's total number). The annual average concentrations of PM_2.5, PM₁₀, SO₂, CO, and NO₂ declined while that of O₃ increased. (3) The impact of China's city network on environmental quality were mainly due to the spatial spillover effect brought by the externality of the city network. The enhancement of the city's degree centrality could increase the ability of the borrowing size and borrowing technology to gain development advantages, thereby promoting the improvement of environmental quality. (4) The upgrade of city's degree centrality has improved the environmental quality of the eastern, central and northeastern regions, reducing the annual average concentration of PM_2.5, PM₁₀, SO₂ and O₃, but that of CO was increasing, while the enhancement of city's betweenness centrality has improved the environmental quality of the western region and significantly reduced the annual average concentration of NO₂.

The influencing factors of carbon emissions are an important research field that arouses the scholars' concern. Scholars at home and abroad have conducted many case studies and enriched their knowledge. Due to regional heterogeneity in socio-economic development and resource endowments, the research conclusions differ among scholars' results. There is a lack of systematic review and summary for research papers on carbon emissions. Based on the literature review, characteristics of carbon emissions influencing factors were summarized, and the results show that: (1) The influencing factors of carbon emissions have the characteristics of time effect, space effect and spatial scale effect. The influencing factors change in the degree and direction over time, region and spatial scales. (2) The time effect, space effect, and spatial scale effect of emission factors are related to the rapid economic development of China, the regional differences in economic development levels, and the coupling of economic development on temporal and spatial scales. (3) To capture the characteristics of emission drivers, future research need to be based on regional development direction, regional classification management and control, and spatial downscaling. Territorial function is the integrated expression of natural carrying capacity, socio-economic level and development potential. Due to the different functional positioning of urban, agricultural and ecological zones in the development and protection pattern of territorial space, industrial agglomeration and population distribution have their own characteristics, which lead to differences in energy-related carbon emissions. It is an important theoretical and practical attempt to carry out classified management and control of carbon emissions with the Major Function-Oriented Zones as impetus.

Coastal zone is the area with the strongest land-sea interaction. It is also the area with the largest scale of land development and utilization, the most complete types, the highest intensity, and the most fragile ecological environment. With the continuous advancement of urbanization and industrialization in coastal areas, the pressure on resources and the environment in these areas is increasing. The implementation of coastal space use control has become effective solutions to the problems of regional ecosystem degradation, environmental pollution, disaster threats, and inefficient use of resources. The negative effects produced by the development and utilization of the coastal zones have typical cross-regional characteristics. Therefore, the use control of a single space or element cannot solve the resource and environmental problems of the coastal zones. This requires a global, holistic and systematic thinking to implement use control, which is also an important reform request for the regulation of coastal space use. Based on the above thinking, this article introduces the theory of inter-regional negative externalities, and shifts the research object from space and space utilization to the evolution process of man-land (sea) relations that accompany space utilization. First of all, the article sorts out several typical manifestations of inter-regional negative externalities produced by the use of coastal space. In order to weaken the microscopic differences of geographic units, judge and analyze the evolution process of inter-regional negative externalities from a macro perspective, the coastal zone space is divided into adjacent shore land system, nearshore sea area system and inland regional system in this article, and on this basis, the relationship and characteristics of coastal zone regional systems are analyzed; secondly, from the perspective of the role of regional systems, it is proposed that the mechanism of coastal space use control is based on the constraints of the sustainable development of space. According to the protection needs of the recipient area, the control concept of determining the land by the sea or determining the sea by the land is selected, and finally by imposing various control measures to reduce the impact of the main area. The specific measures of the environmental impact of the recipient area include main area control, media control, transition area (action interface) control, and recipient area control; finally, the ideas for improving the system of coastal space use control, including the improvement of land-sea integration policy recommendations such as zoning control, shoreline classification control and balance of occupation and compensation, delineation of special control lines, total land source pollution control, etc., are expected to provide theoretical support and decision support for improvement of the coastal space use control system.

The rural settlement is considered as the spatial reflection of rural geographical functions, and its internal land use function and structure always change with the socio-economic development. “Transition” has been the major characteristics of the land use structure of rural settlements in China. Based on the rural vitalization strategy, this paper tries to firstly clarify the definition of land use structure of rural settlements, and then explore the transition laws of land use structure of rural settlements by following the research framework “process-types-mechanism-optimization”. This paper has combined the research of rural settlement transition and the changing times. The results show that (1) by analyzing the changing process of composite relationship between typical land-use types within rural settlements, the land use structure transitions can be divided into three types, i.e., external non-agricultural type, internal rurality type, and hollow declining type; (2) urbanization, rural industrialization, and rural modernization proposed by rural vitalization strategy can be regarded as the pull and push forces for this transition by changing the population, land, capital and technology elements flow and efficiency of resource allocation between urban and rural areas, thereby affecting the directions, types and results of land use structure transitions. In the future, guided by the rural vitalization strategy, we should optimize the land use structure by type conversion, land use efficiency enhancement, and policy guarantee. This paper can enrich and innovate the research of rural settlements transition and optimization theoretically, as well as provide scientific support for the village's planning and rural vitalization practically.

In the age of globalizing knowledge economy, inter-country scientific collaborations are more and more frequent. Therefore, the globalization and networking characteristics of scientific research activities are increasingly prominent. The scientific collaboration between two countries does not only rely on the bilateral relationship between, but also is influenced by the structural effects of the network itself. However, the endogenous structural effects are ignored in the literature on the evolution of knowledge network. Based on the internationally collaborative papers from the Clarivate Analytics' InCites database in the period 2000-2019, this study uses social network analysis and stochastic actor-oriented model to explore the structure, dynamics and determinants of global scientific collaboration network. Results show that the size of the network has expanded, the number of nodes and ties in the network has substantially increased, and the densification of the network has strengthened over time. Distinctive characteristics of the network is typically small-world nature and partially scale-free distribution, and there is a significant trend towards decentralization in the collaboration network. The whole network displays the co-existence of hierarchical “star-shaped” structure and heterarchical “universal” structure. China moves up from the periphery to the core, and the network is evolving from a single-center dominated by the United States to the double center including Sino-US, the bilateral partnership between China and the United States becomes the most importantly bilateral collaboration in the world. In addition, stochastic actor-oriented model indicates that transitivity and preferential attachment positively drive the evolution of scientific collaboration network. Geographical proximity and cognitive proximity have a positive and significant effect on the formation of international collaboration. The dynamic mechanism of the global scientific collaboration network is facilitated by country size. Meanwhile, common language, post-colonial links, and international students play an important role in the dynamics of global scientific collaboration network. Besides, we find that the effects of transitivity, geographical proximity, cognitive proximity and country size have increased, while the impact of preferential attachment has waned over time.

Development zones in China have been undergoing a series of transformations in the past decades, termed as the “three transitions”. This is followed by a new wave of transformation observed in some well-developed development zones in regions such as the Yangtze River Delta, evidenced by the formation of networks among these development zones at the regional level. These cross-boundary connections usually take the forms of industrial cooperation, the co-built industrial parks and policy sharing, which allows development zones to optimize the allocation of resources and thus improve productivity. While studies have revealed valuable insights into the cooperation and connections among development zones, few have investigated the phenomenon with the consideration of its relationship with the “three transitions” and thus fail to reveal its significance to the spatial transformation in contemporary China. In addition, previous studies performing quantitative measurements of these networks tend to use methods such as gravity models to approximate the connections, and less attention has been paid to more specific and tangible connections such as production chains and transport networks. Also, few studies have examined the factors affecting the formation and the evolution of these networks, e.g. how do distance, administrative level, and the GDP of cities where the development zones are located shape the network. In this context, this paper situates the formation of the networks in the series of previous transitions and proposes the emergence of the “fourth transition” of development zones in China. Following this, we take the state-level economic and technological development zone in the core area of the Yangtze River Delta region as an example and measure the network among these zones by adopting a corporate organization approach that has been widely used in intercity network research. After a brief description of its evolutionary characteristics with the application of social network analysis, we explain its micro-mechanism using stochastic actor-oriented models. The result shows that the “fourth transition” serves as a strategy of development zones to break through the limit of urban boundaries and seek new opportunities at the regional scale, which can also be understood as a new approach to regional integration. In the Yangtze River Delta region, the growth of the network is accelerating and the core-periphery pattern has been more evident over time, with the better-connected development zones concentrated in northern Zhejiang and southern Jiangsu. This is influenced by factors such as network effects, the attributes of development zones and the city in which they are located, as well as the geographical proximity of parent enterprises to development zones.

Human capital is the synthesis of knowledge, skills and health level embodied in workers, which is of great significance to understand the spatial and temporal pattern of regional economic development in China during the period of innovation-driven and people-oriented construction. However, for a long time, the spatial measurement of human capital is facing many challenges. For example, the availability of data is quite low, the evaluation index cannot cover the connotation of human capital, and the research scale is mostly at the provincial level. This study attempts to construct a multi-index comprehensive evaluation system of human capital level based on the dataset of the fifth and sixth China population censuses to evaluate regional overall human capital level in China between 2000 and 2010. Using the method of Global Principal Component Analysis and Exploratory Spatial Data Analysis, this study analyzes the spatiotemporal distribution and change of regional overall human capital level in China at the provincial, municipal and county scales, respectively. The results show that the level of human capital in China is characterized by “high in the Northeast and low in the Southwest, and the high level of human capital areas are distributed in dots or blocks”, showing the obvious space agglomeration. Besides, the level of human capital has scale effect, and the level of human capital in county scale has the highest degree of difference and spatial agglomeration. During the study period, the level and the stock of human capital increased as a whole in China, but about 11 percent of counties' human capital level showed a decreasing trend. The research results provide a new method for measuring the level of human capital on the different spatial scales, and provide support for human capital research and optimizing allocation of human capital from the spatial perspective.

The continuously growing internal migration in China has not only profoundly changed the population distribution pattern, but also become a key factor affecting the regional variation in population structure, of which the significantly varying level of aging is a typical case. In order to quantitatively estimate the region-specific aging effect of migration, this study developed a methodological framework to decompose the contribution of migration to regional aging into scale effect and age structural effect. The effects of in- and out-migration could be examined separately and comprehensively by using this method. Empirical analysis was conducted at the prefecture level with focuses on the spatial patterns and underlying mechanisms of the separate and overall effects. The estimation results revealed that migration has accelerated the aging process in most prefectures whereas alleviated it in a few regions. The reducing effect of population inflow and the enhancing effect of outflow on aging were not necessary as commonly expected in the existing literature. Remarkable regional variation was found in the aging effect of migration. The well-known Hu Huanyong Line was a distinct divide of the aging effect due to its significant role in the geography of China's internal migration. The aging process was slowed down greatly by massive in-migration in coastal mega-regions, inland provincial capitals and other regional central cities, as well as most western prefectures. In contrast, the process was accelerated in the middle and upper reaches of the Yangtze River and the Huaihe River Basin with large-scale out-migration. The overall effect was contributed and the spatial patterns were shaped jointly by the scale effect and structural effect with the dominance of the former. Significance of the latter emerged as the effects of in- and out-migration were evaluated separately. Moreover, the two effects manifested diverse importance and modes in different areas. Finally, a typological analysis was conducted to identify the most typical features, mechanisms, and future trends of aging in various regions across the vast territory of China. These empirical studies and results demonstrated the rationality and effectiveness of this novel methodological framework. The limitation of this decomposition method and the future study to improve it was discussed in the end.

With the interaction of environmental changes, technological progress, and urbanized life, the supply-demand process of daily activity space needs and can be more resilient, but the existing study is rarely involved. Therefore, this study focuses on the main contradiction of China's social and economic development, excavates the connotation of urban resilience under the scenario of supply-demand contradictions between daily activities and the environment, and then constructs an organically integrated theoretical framework and evaluation index system of urban resilience. Finally, taking the central urban area of Nanjing as an example, and relying on the support of geographical big data, the comprehensive evaluation on spatial characteristics of daily activity-environment system resilience is carried out. The main conclusions are as follows: (1) The structure of supply and demand of resilience factors between activities and environment as well as between quantity and quality is out of balance, and the imbalance and insufficiency of supply and demand exist simultaneously and restrict each other. (2) The spatial distribution of activity resilience and environmental resilience is significantly different, and the level of their supply and demand is low, as well as the degree of their mutual matching, which resulted in a spatial pattern of low-level spread of daily activity-environment system resilience. (3) The spatial support or matching role among activity resilience, environmental resilience, and system resilience has not been fully exerted, leading to serious differentiation of supply and demand of daily activity space, and lack of continuous benign interaction in spatial distribution. Therefore, the overall dynamic synergistic optimization of the supply and demand network of daily activity space should be promoted according to the evolution stage of resilience. In short, for urban resilience research, this paper has some reference value for the expansion of cross-fields, the integration of theoretical frameworks, the optimization of evaluation methods, and the implementation of governance concepts.

China has witnessed rapid growth of its consumption economy and shopping needs in recent years. The rules of residents' shopping travel have positive significance for arranging commercial space, planning traffic network and improving citizens' personal welfare. Thus, the residents' shopping trip have drawn increasing attention. Previous studies intensively investigated the individual and microscale shopping travel behaviors of residents. However, there is a lack of national-level research on the shopping trip patterns of residents in China. The purpose of this study is to fill this research gap. By using the nationwide time-use survey data of 49,673 respondents in nearly 300 sites in urban and rural areas in 29 provincial-level regions across the country, this paper systematically explores the characteristics and determinants of shopping travel behaviors. GIS spatial analysis is applied to investigate the characteristics of participation rate, shopping duration, and traffic travel time for shopping. A discrete choice model is used to explore the influencing factors of Chinese residents' characteristics of shopping travel behaviors. The study found that the shopping participation rates of the rural areas are lower than that of the cities, and the rate of the western region is lower compared with the eastern coastal areas, but the shopping duration is reversed. Residents in Qinghai, Inner Mongolia, Chongqing, and Yunnan have the longest travel time for shopping. Residents' shopping travel behaviors are affected by residents' individual attributes, the family attributes and location conditions of residents' family. Finally, from the perspective of infrastructure construction and shopping center planning, this paper puts forward countermeasures and suggestions for the optimization of urban and rural spatial layout and traffic development.

This paper uses the commercial gentrification space of Daci Temple Community in Chengdu as the case. Based on Pierre Bourdieu's ‘field’ theory, it analyses the interest demand and capital acquisitions from the different actors of local government, developers, gentrifiers, residents, surrounding merchants and tenants. Then, it explores the influence mechanism between commercial gentrification and surrounding old neighborhoods. Using two qualitative research methods of participant observation and semi-structured interview, the empirical research findings show that commercial gentrification and surrounding old residential areas constitute a gentrification field, where different actors acquire and accumulate their own capital to establish social practice status. The gentrification core field composed of high-end consumption space where the local government and private developers unite. Specifically, the former pursuits the symbolic capital brought by beautification image driven by the development of the global city and national central city, while the latter accumulates maximum economic capital. Gentrifiers promote the development and consolidation of commercial gentrification in the process of pursuing a lifestyle consistent with their own social attributes. However, the residents are in a weak position in the process of gentrification, which becomes the subject of capital outflow. In the marginal field, the surrounding merchants begin to reconstruct businesses to cater to gentrifiers. Besides, with the new consumption space in the core field, the surrounding tenants have acquired economic and social capital in the whole gentrification field. Therefore, this paper reveals two important capital logics in the field. The core field of gentrification is promoted by the interest alliance formed by the local government, developers and gentrifiers, which reflects a top-down global capital logic. The marginal field is constructed by residents, surrounding merchants and tenants, which is presenting a bottom-up local capital logic. This is because the marginal field is influenced by the core field, forming a dynamic mutual relationship with the core field. Finally, this research fills the theoretical gap for the impact of China's commercial gentrification on surrounding residential areas, and in light of the practice value for the renovation of commercial space in urban centers.

In the strategic background of high quality integration in the Yangtze River Delta (YRD), it is a feasible choice to build an inter-regional environmental collaborative governance system to improve the effectiveness of air pollution control in the region. This paper constructed an evaluation system of coupling degree of air pollution regulation from three dimensions: policy documents, implementation process and governance effect of environmental regulation, and then explored the spatio-temporal evolution characteristics of coupling degree of air pollution regulation in 41 cities in the YRD from 2003 to 2019. On this basis, the cities in the YRD are divided into regional collaborative governance groups, and the synergy degree of air pollution control is measured respectively, thus the influencing factors of collaborative governance of air pollution in the YRD are explored. The results show that: (1) The coupling degree of air pollution regulation in all the cities shows the characteristics of agglomeration development, with Shanghai being the highest, followed by Zhejiang province and Jiangsu province, and Anhui province being the lowest, while the regional differences are narrowing. (2) The synergy degree of air pollution control in the YRD as a whole was low and showed a slow rising trend in the fluctuation, but the synergy degree of air pollution control remained at a high level after the division of regional collaborative governance groups. (3) The results of influencing factors analysis show that the differences in opening up, public transportation and greening construction between regions have significantly inhibitive effect on the collaborative governance of air pollution in the YRD, while the differences in economic growth and technological innovation have significantly positive effect.

Based on the comprehensive evaluation method combining fixed base range entropy weight method and fixed base equal weight assignment method, kernel density estimation and exploratory spatial data analysis methods, this paper analyzes the spatio-temporal evolution characteristics of public health level of 284 cities in China from 2003 to 2018, and uses the generalized spatial two-stage least square method to investigate its influencing factors. The results show that: (1) During the study period, the urban public health level is on the rise as a whole in China, but the difference of public health level among cities has expanded, and there is always a phenomenon of multi-level differentiation. (2) The kernel density curves of the four plates have their own evolution forms in the position of gravity center, the height of main peak, the number of wave crests, the length of trailing and the thickness of trailing, which is the result of the coupling and superposition of time characteristics and regional characteristics. (3) There are positive spatial spillover effect and spatial “Peer Effects” in China's urban public health level, and the spatial agglomeration type has transformed from LL type to HH type. (4) Income level, population density, technological progress, industrialization and health system reform have an impact on urban public health, but the impact of various factors on different regions is heterogeneous.

In January 2021, the COVID-19 outbreak in Xiaoguozhuang Village of Shijiazhuang, the first COVID-19 public health emergency in the rural areas of China. Based on the individual trajectory data in 14 days of 941 confirmed cases, taking the transmission network structural analysis and the epidemic transmission dynamics analysis as the methods, the COVID-19 transmission network from the three aspects is deconstructed: epidemic points formation, types of outputs, and regional expansion evolution. Compared with the COVID-19 transmission network of Beijing Xinfadi Market and Dalian Kaiyang Seafood Company, the conclusions are as follows: (1) The numbers of epidemic points and types are large. In the approximate exposure time, new epidemic points will be formed simultaneously with the central city under the background of rapid urbanization. Still, high community activity leads to the formation of co-exposure to epidemic points; short distance "pendulum moves" leading to more extensive individual trajectory density, and finally resulting in the risk of temporary exposure of epidemic points. (2) It has the significant individual-individual contact infection characteristic and output chain relationship characteristic. The secondary outputs of the rural areas are due to the multigenerational family transmission, which is not seen in the urban cities. (3) Compared with the regional expansion of urban cities, the rural areas are manifested by a longer transmission period, caused by the long occult time of outbreaks and the relatively high relative risk of symptomatic confirmed cases in the rural areas. Finally, three suggestions are put forward, enlarging the management space from the terminal areas to adjacent areas around airports, and then implementing delay management on the overflow personnel based on time shift due to carrying the virus from potential epidemic points and buffering isolation area according to the range of risk changes. The deconstruction network of public health emergencies is a beneficial exploration and will provide a basis for improving the resilience of public health networks in rural areas.

Under the long-term influence of wind erosion, land surface coarsening on the Northern Tibet and Southern Qinghai Plateau is obvious. In this paper, the surface soil (0-1 cm deep) and shallow soil (1-10 cm deep) were systematically sampled in an east-west directional survey transect. By grain-size composition measurement and constructing a wind erosion coarsening index (WECI) that can depict the soil wind erosion coarsening degree, wind erosion coarsening characteristics of the land surface on the plateau were analyzed. Results show that the contents of coarse particles such as gravel, very coarse sand, and coarse sand in surface soil are higher than those in shallow soil, and the contents of coarse particles decrease gradually from west to east. On the contrary, compared with shallow soil, the contents of fine particles such as clay and silt decrease significantly in surface soil and increase gradually from west to east. From the eastern alpine meadow region (average WECI = 1.05) to the central alpine steppe region (average WECI = 1.47) and the western transition region between the alpine steppe and desert steppe (average WECI = 1.77), the degree of land surface coarsening caused by wind erosion aggravates. The fractal dimension and soil texture coarsening indexes commonly used in existing research are static indicators that can describe the soil texture status but cannot measure the change in surface soil particle composition caused by wind erosion. The wind erosion coarsening index constructed in this paper overcomes the above shortcomings and has the basis of wind erosion dynamics.

Exploring the characteristics and causes of extreme climate change in the Niyang River Basin under global warming has important significance for scientific support of extreme climate disaster prevention and ecological security in Tibet. Based on the precipitation and temperature data of the Niyang River Basin from 1960 to 2019, we used the extreme climate index method, Sen's slope method, Mann-Kendall tendency and abrupt change test and GIS spatial analysis method to explore the spatio-temporal distribution characteristics of extreme climate in the basin in the past 60 years from the perspectives of precipitation and temperature. Combined with atmospheric circulation factors, we used the Geodetector method to investigate the possible causes of spatio-temporal characteristics. The results showed that the Niyang River Basin showed a trend of warming and wetting on the time scale. Precipitation amount, precipitation intensity, and the number of days of extreme precipitation all showed an increasing trend. High-temperature and low-temperature extremes all showed an increasing trend, and the number of low temperature days showed a decreasing trend. On the space scale, there was an obvious spatial heterogeneity in the study basin. The extreme precipitation overall gradually decreased from the east to the west, and the extreme temperature overall gradually cooled from the southeast to the northwest. As a water vapor channel, the Niyang River had effects of warming and heat-preserving, thus the extreme climate indexes showed continuous extreme points along the river. The Subtropical High and the Qinghai-Xizang High had a positive effect on the warming and humidification of the Niyang River Basin, while the Polar Vortex and North Atlantic Oscillation were the opposite. Topographic factors represented by slope and underlying surface factors represented by NDVI were the most important environmental factors that respectively influenced the spatial distribution of extreme precipitation and extreme temperature. Elevation played an important role in the spatial distribution of both extreme precipitation and temperature.

The study of spatio-temporal variation of dissolved carbon in regional groundwater is of great significance for understanding regional material cycle and energy transfer and promoting regional ecological sustainable development. In this study, groundwater, river water and lake water samples were collected to examine the characteristics of dissolved carbon in groundwater around the Qinghai Lake during the freezing and thawing periods, investigate the characteristics of dissolved carbon in different types of groundwater and its responses to the freezing and thawing periods, and reveal the difference characteristics and influencing factors of dissolved carbon in different water bodies around the lake. The results showed that the dissolved inorganic carbon (DIC) of groundwater, river water and lake water in freezing period was higher than that in thawing period, while the dissolved organic carbon (DOC) of groundwater, river water and lake water in freezing period was lower than that in thawing period. DIC was the main dissolved carbon in groundwater, river water and lake water, which accounted for 92% of dissolved carbon. The mean content of DIC in groundwater was relatively high under the hydrogeological conditions of bedrock fissure water, moderate water volume and shallow burial water, while the mean content of DOC was relatively high under the hydrogeological conditions of bedrock fissure water, abundant water volume and shallow buried water. DIC in groundwater was greatly affected by freeze and thaw process under the hydrogeological conditions of gravel bed in lakeside plain, diving in muddy sand and moderate water volume, while DOC was greatly affected by freeze and thaw process under the hydrogeological conditions of bedrock fissure water and poor water volume. DIC and DOC in lake water were much higher than those in river water and groundwater. DIC in river water was lower than that in groundwater in both the thawing and freezing periods, while DOC in river water was higher than that in groundwater in the thawing period and lower than that in groundwater in the freezing period.

Terrain Complexity index (TCI) is a digital representation of the external morphological structure of the regional surface. The TCI can characterize the diversity of slope units and the complexity of their combination forms, and also map the process of "imprinting" the Earth's internal and external forces on the surface. The objective description and quantitative expression of TCI can provide an important basis for topographic and geomorphological theoretical studies such as definition, characterization, and differentiation of surface morphology. The unique mountain-basin geomorphic structure in Xinjiang provides an ideal place for geomorphological research. This paper is based on the "inverted pyramid filter system" to gradually filter micro and macro slope factors and determine the weights to build a TCI model. The mean change point method was used to determine the optimal window of TCI in Xinjiang, analyze the spatial heterogeneity of TCI of different geomorphic units, and further explore the contribution of different forces to TCI. The results show that: (1) The TCI model is objectively screened and scientifically combined with correlation analysis, cluster analysis, coefficient of variation method, and principal component analysis so that the TCI model has overall objectivity and independent validity. (2) The TCI is based on the global Digital Elevation Model (ASTER GDEM, 30 m) terrain data (V2), and the TCI of the whole of Xinjiang is between 0.13 and 46.36 under the optimal window (14×14). The peak value of the TCI area of the same geomorphic type is similar to that of the basin, and the slope, skewness, and kurtosis of different geomorphic types can be compared to distinguish them. Local topographic differentiation, such as independent peaks and deep canyons, can be better characterized in longitude and latitude, and TCI equal to about 1 can be used as the boundary value between plain and mountain geomorphic units. When TCI is greater than 2 in elevation division, it is the beginning of the oscillation elevation region of each mountain system (mountain group), and the TCI curves at the foothills are significantly different. (3) TCI can better reflect the traces left by different exogenous forces on the surface, and to a certain extent, it can also represent the contribution of exogenous forces to different genetic geomorphic types. This study provides the theoretical basis and scientific method for the formation reasons and morphological characteristics of topography and geomorphology in Xinjiang and provides practical guidance for topography and geomorphology research, ecological environment impact, and regional development evaluation.

In recent years, contact crime represented by theft and non-contact crime represented by telecommunication network fraud are both increasing, seriously affecting social stability and people′s property security. Previous studies have paid less attention to the spatial and temporal stability of different types of crime distribution patterns, and no research has yet compared the spatio-temporal stability of contact crime and non-contact crime. In the meantime, current studies also failed to propose spatial joint prevention and control strategies for different types of crime. This study takes HT District of ZG City as an example, takes the community as the analysis unit, uses kernel density estimation and space-time transition measure method to compare and analyze the spatio-temporal distribution characteristics and monthly stability of the spatial distribution pattern of theft and telecommunication network fraud in 2017. After that, we refer to the idea of spatio-temporal transition to improve the method of space-time transition from the perspective of crime prevention and control, and then identified the spatial prevention and control types of theft and telecommunication network fraud. Based on this, combined with the method of two-step cluster to recognize the joint prevention and control spatial types of two kinds of crime. The findings are as follows: (1) The spatial and temporal stability of the two types of crime is different. The spatial distribution pattern of theft crime is stable and its spatio-temoral transition indexes of adjacent months are more than 50%. However, the spatial distribution pattern of telecommunication network fraud is unstable and fluctuates greatly on the whole. What it is worth to mention is that the pattern is especially stably in February and March. (2) Four spatial types of joint prevention and control of these two types of crimes are recognized, which are respectively "two types of crime without prevention and control communities", "two types of crime neighborhood prevention and control communities", "theft crime hotspot prevention and control, telecommunication network fraud without prevention and control communities" and "theft crime coordinated prevention and control, telecommunication network fraud comprehensive prevention and control communities". This study is helpful to understand the similarities and differences between contact crime and non-contact crime in time and space, and provide guidance for police prevention and control.

As the spatial carrier of people's daily behaviors, the street network and behaviors therein constitute the main spatial environment of street network, which affects criminal behavior. Previous studies have shown that there are frequent cases of robberies and thefts in the streets, and the street network pattern and routine activity subjects are both related to crime. However, there are few in-depth explorations of such a relationship. Based on the police patrol area unit of the original DP District of HS City, this paper has adopted spatial analysis and statistical analysis methods to analyze the road network data, demographic data, mobile phone signaling data and other relevant data in order to explore the relationship between crime and street morphological characteristics including geometric and topological form, the relationship between crime and routine activity subjects including dynamic population and static population, and the impact of the street network on robberies and thefts. The results have shown that the factors affecting thefts and robberies in the street network are quite different. The factors affecting the theft crime are more complex. "X-cell" street network, road network density, road network permeability of low-speed traffic, static population density and dynamic population density all have an important impact on thefts. Only the branch density has a negative effect, and the rest of the factors have a positive effect. "T-cell" street network, density of actual residents and migrants in static population are related to robberies. But the street network pattern has not shown a significant correlation with robberies. In general, the street networks with more main roads, better accessibility, higher population density, and higher population mobility are prone to thefts. The street networks with many migrants are prone to the robberies. In addition, the findings of this study can also make certain extensions to the crime pattern theory. Since the accessibility of street network often brings risks, it is proposed at the end of the paper that it is imperative to consider how to reduce the crime risks as much as possible by regulating or improving the overall spatial environment of street network during the planning and construction of a safe street network environment in the future.

This study aims to identify the main types, their magnitudes of influence, and their characteristics of regional heterogeneity of theft places, and take the lead in discussing the application of geographical detector in the field of crime geography analysis. Using criminal judgement, Points of Interest, Location-based Service data, road network, census data, housing data, and other data in the central urban area of Beijing and taking the 1 km×1 km square grid as our spatial analysis unit, this research demonstrates that thirty-seven types of urban facilities belong to the major crime generators, crime attractors or crime enablers at the global level, and the edge areas of roads, administrative districts and land uses are also proved to be evident theft locations. Among them, the more influential theft locations are more aligned with the crime generating conditions proposed by crime pattern theory, including accessible crime target and lower risk of arrest. Second, as stated by social disorganization theory, if the level of social disorganization composed by mobility factor and housing factor decreases, the number of theft location types as well as their impacts will gradually diminish. But except for the low social disorganization districts, the rankings of relative influence of various facilities and edge areas on theft crime remain relatively stable. Third, geographic detector has the advantages of no linear hypothesis, no collinearity problem, clear physical meaning and so on. But owing to the neglect of the potential interference by confounding factors, geographical detector would probably overestimate the impacts of independent variables. It can be testified by the moderate correlation between the rankings of the overall influence of theft locations obtained from the negative binomial regression and those calculated by the geographical detector. We suggest that combining elimination control method with geographical detector is a feasible path to achieve robust results, so classification discussion after grouping units with similar confounding factors is essential to overcome the potential endogeneity problem if we use geographical detector in crime geography as well as other sub-fields of human geography.

It has been found that the type of community housing has an important impact on the spatial pattern of burglary in urban areas. However, few scholars have explored the difference of the impact of different housing types in different degrees of population mobility on burglary. This study takes ZG city, a coastal city in southeast China, as a research area. It is based on theories of routine activity theory, crime pattern theory, rational choice theory and social disorganization theory. This paper, taking community as the unit of analysis, adopts data of burglary, the sixth national census and Point of Interest (POI). The spatial lagged negative binomial regression method is used to analyze the impact of the interaction between community population mobility and housing types on the spatial pattern of burglary. Among them, the population mobility factors were extracted based on the proportion of migrant population and the proportion of renting houses. The results show that population mobility has a significant positive impact on burglary rate. There is a significant positive effect of the proportion of owner-built housing on the rate of burglary, and the proportion of former public owned housing and commercial housing has a significant inhibitory effect on the burglary rate. In addition, the impact of affordable housing on burglary is not significant. The results of the interaction variables found that the interaction coefficients of population mobility with different types of housing variables are varied. Among them, the interaction of population mobility with self-built housing, affordable housing and former public housing has a significant promoting effect on burglary rate, indicating that the higher the degree of population mobility, the greater the impact of these three types of housing on burglary. Nevertheless, the interaction effect of population mobility and commercial housing is not significant. This study proves that population mobility can further mediate the effects of different types of housing on burglary, and suggests that we should pay attention to the impact of the degree of population mobility in the community where different types of housing are located when discussing the relationship between different types of housing and burglary.