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Housing prices in China have experienced rapid growth in recent decades, and land finance has long been discussed as an important factor in this growth. In this paper, we explore the interactions among housing prices, land transfer revenue and infrastructure investment from the perspective of government revenue and expenditure. Based on the panel data of 35 large and medium-sized cities in China from 2000 to 2017, the empirical results show that land transfer revenue, infrastructure investment and housing prices are causally related and result in positive feedback. The grouped regression results show that infrastructure investment has greater impacts on housing prices in eastern region cities than in the other cities. In contrast, in the central and western regions, land sales revenue has a greater impact on housing prices, indicating that cities in less-developed areas are more dependent on land finance than are those in more developed regions. Finally, we use the vector error correction model (VECM) to add control variables for robustness testing. The results show that land transfer income and infrastructure investment have a positive impact on housing prices. Our results provide some references for the stable development of housing markets in China. [ABSTRACT FROM AUTHOR]

Based on the data of 278 prefecture-level city panels in China from 2008 to 2020, this paper presents the policy of innovative pilot city as a quasi-natural experiment. It is found that (1) the implementation of innovative urban policy can significantly improve the level of science and technology entrepreneurship, but the pilot policy has a time lag effect and has a continuous promoting effect since the third year. (2) For large cities, areas with high levels of economic development, central and eastern regions and cities with high new infrastructure, innovative cities can improve the level of technological entrepreneurship; (3) Innovative cities improve the level of technological entrepreneurship by improving the incubator of technological enterprises and strengthening the flow of human capital; (4) The effect of the establishment of innovative cities on the level of technological entrepreneurship mainly shows that the siphon effect does not show radiation effect, and this siphon effect mainly improves the level of technological entrepreneurship by increasing the number of incubators of technological enterprises. [ABSTRACT FROM AUTHOR]

Among the critical global crises curbing world development and sustainability, air quality degradation has been a long-lasting and increasingly urgent one and it has been sufficiently proven to pose severe threats to human health and social welfare. A higher level of model prediction accuracy can play a fundamental role in air quality assessment and enhancing human well-being. In this paper, four types of machine learning models—random forest model, ridge regression model, support vector machine model, extremely randomized trees model—were adopted to predict PM2.5 concentration in ten cities in the Jing-Jin-Ji region of north China based on multi-sources spatiotemporal data including air quality and meteorological data in time series. Data were fed into the model by using the rolling prediction method which is proven to improve prediction accuracy in our experiments. Lastly, the comparative experiments show that at the city level, RF and ExtraTrees models have better predictive results with lower mean absolute error (MAE), root mean square error (RMSE), and higher index of agreement (IA) compared to other selected models. For seasonality, level four models all have the best prediction performances in winter time and the worst in summer time, and RF models have the best prediction performance with the IA ranging from 0.93 to 0.98 with an MAE of 5.91 to 11.68 μg/m3. Consequently, the demonstration of how each model performs differently in each city and each season is expected to shed light on environmental policy implications. [ABSTRACT FROM AUTHOR]

The phenomenon of polarized development among regional cities has sparked extensive contemplation and indicated a need for research on multi-source regional networks. However, such research faces two obstacles: the absence of quantitative measurement of differences in network structures and the lack of a thorough examination of the degree of city clustering and the dynamics of community composition in hierarchical networks. Thus, we identified 16 cities in the Chengdu–Chongqing Economic Circle (CCEC) as the spatial units to examine the spatial network structures of population, resources, and transportation and the integrated spatial network structure. Using social network analysis, this paper describes the structural characteristics of the three networks (population, resource, and transportation), followed by an analysis of their collective and hierarchical network clustering characteristics, and explores the driving mechanisms and factors that make up each network model. Our results show the following: (1) All three networks exhibit an "east dense, west sparse" characteristic, but there are differences in the layouts of the core cities in terms of the three networks. (2) The clustering characteristics of the hierarchical networks are more pronounced than those of the overall network. The results of the analysis combined with the network formation mechanisms can help effectively plan the future coordinated development of the CCEC. [ABSTRACT FROM AUTHOR]

The inflow of foreign R&D has brought vigor and vitality to the development of the high-tech industry (HTI). Using the panel data of HTI in 23 provinces (autonomous provinces and municipalities) in China from 2007 to 2016, this paper firstly calculates the Moran index of HTI's innovation performance (IP), and finds a spatial agglomeration effect. After rigorous testing, we determine the most suitable spatial metering model. Finally, the spatial effect is further decomposed into three kinds of effects: direct effect, indirect effect, and total effect. This paper studies the impact of foreign research and development (R&D) on IP of HTI and its spatial spillover effects. According to the research, foreign R&D has a significant role in promoting IP of HTI in China, and has specific spatial spillover effects. Significantly, foreign R&D has substantial positive spillover effects of space. When IP of HTI is measured by product innovation, there is no obvious space overflow. However, panel regression showed a significant positive effect. In terms of the influence on product IP of HTI, foreign R&D plays an almost equal role as local R&D. In terms of the impact on technological IP of HTI, foreign R&D input plays a positive role. It has a spatial spillover effect, the degree of impact is lower than that of domestic R&D input. Local governments should formulate relevant policies to encourage the fluidity of technical knowledge and overcome the sticky problem of foreign R&D technical knowledge, which is an essential aspect of absorbing foreign R&D technical knowledge in the future. [ABSTRACT FROM AUTHOR]

There are urgent ecological and environmental problems in the process of the utilization of urban construction land, promoting green utilization of construction land is conducive to urban sustainable development and high-quality economic development. Based on the panel data of 108 prefecture-level and above cities in the Yangtze River Economic Belt, China from 2003 to 2017, this paper uses the super-efficiency SBM model to measure the green efficiency of urban construction land (GEUCL), analyzes its spatial–temporal evolution characteristics, and constructs the spatial autoregressive model to study its spatial spillover effects from the perspective of urban hierarchy. It is found that, in terms of temporal variation, the average efficiency value shows a fluctuating upward trend during the study period, rising from 0.27 in 2003 to 0.39 in 2017, the cumulative growth rate is 44.44%, with an average annual growth rate of 3.14%. In terms of spatial distribution characteristics, during the study period, the number of medium-efficiency and high-efficiency cities increases significantly, while the number of low-efficiency cities decreases sharply; high-efficiency cities always present scattered distribution, while medium-efficiency cities change from scattered distribution to agglomeration distribution. In addition, GEUCL has significantly positive spatial spillover effects between neighboring cities of different grades and between neighboring cities of the same grade, among them, the increase of GEUCL in higher-grade cities has significantly positive spatial spillover effects on that in adjacent lower-grade cities; the increase of GEUCL in lower-grade cities has significantly positive spatial spillover effects on that in neighboring higher-grade cities; GEUCL has significantly positive spatial spillover effects between neighboring cities of the same grade. [ABSTRACT FROM AUTHOR]

Given the significant role of the Ningxia Urban Agglomeration along the Yellow River in reshaping the urban network and promoting coordinated development in the upper Yellow River region of China, this paper takes enterprise flow as the explicit manifestation of the regional urban network and interprets the evolution of the regional urban network structure and its influencing mechanisms through the different types of enterprise flow. The results indicate the following: (1) The external network is primarily focused on outflow investments towards North China, East China, and Northwest China. The overall inflow sources form a multi-origin structure dominated by North China and East China. Jinfeng and Xingqing serve as core hubs for enterprise exports in the external network and destinations for incoming enterprises. However, in terms of productive manufacturing connections, there is a spatial organizational pattern driven by multiple cities. (2) In the internal network, there is a concentric connection structure centered around Jinfeng and Xingqing. The productive service connections are relatively active, while the productive manufacturing connections are relatively concentrated between Jinfeng, Xingqing, Ningdong, and Lingwu. (3) In the external network, the main feature is the absorption of external elements to foster development momentum. In the internal network, Jinfeng and Xingqing serve as the contact and radiation sources, influencing various nodes. However, the driving capacity is weak. (4) The market demand and coordinated development both demonstrate significant promoting effects on the connections within the external and internal networks. The sluggish adjustment and transformation of the regional industrial structure resulted in a temporary negative inhibitory effect on the development of transformation. The negative impact of urban investment activities and the positive impact of government management are reflected within the internal network. (5) Improvements in urban management and service functions as well as external borrowing can promote connection in different networks. However, borrowing economic activity can have a negative impact in different networks. (6) Industrial agglomeration can promote enterprise connections in different networks and generate spatial spillover effects. [ABSTRACT FROM AUTHOR]

This paper constructs a theoretical model of biased production decisions due to the import of environmental intermediate goods. Additionally, it analyzes the influence of these imports on CO2 emissions based on the trade and CO2 emission data of Chinese prefecture-level cities from 2000 to 2016. Furthermore, it empirically explores how environmental intermediate imports affect CO2 emissions. The study found the following: first, the import of environmental intermediate goods can effectively reduce CO2 emissions; this conclusion still holds under robustness and endogeneity tests. Second, the carbon emission reduction effect related to the import of environmental intermediate goods is affected by differences in geographical location, environmental pollution, sustainable development ability and government efficiency. Third, the mechanism test found that the import of environmental intermediate goods exerts emission reduction effects through the green technological innovation and industrial structure upgrading mechanisms. The conclusions of the research in this article provide a reference for coordinating trade development and environmental protection. [ABSTRACT FROM AUTHOR]

The steady increase in China's ageing population and an upswing in migration among the country's population, on the whole, has caused a continuous expansion of the scale of older migrants. The migration of older adults not only directly affects the well-being of individual families but also significantly impacts the population structure and economic development of the places of origin and destination. Despite this, in China, the various relevant aspects concerning this age group and, in particular, its migration choices and the patterns thereof have only rarely been the subject of sound research. The study presented in this paper seeks to fill this gap; the present study makes use of the microdata obtained from the national population censuses of 2000 and 2010 and the 1% population sample surveys conducted nationally in 2005 and 2015. The findings of the present study were the following: ① During 1995–2015, the efficiency of older adults' migration was significantly higher in the eastern region than in the central and western regions. ② Older individuals migrating to urban areas are increasingly choosing, for their relocation, economically developed, urban areas such as the Yangtze River Delta, Pearl River Delta and Beijing-Tianjin-Hebei region. ③ Relocation of older adults to urban areas was much more than to rural areas. The latter group has a more diverse choice of destination, and the larger migration flow is primarily from developed provinces to relatively underdeveloped provinces. ④ The results of binary logit regression indicated that the factors that significantly and consistently influence the migration decisions of older adults were found to be the following: age, education level, health status, the primary financial resource, children aged ≤ 6 years being members of the household that would receive the migrants, and the average wage of employees. As for the geographical characteristics of the province to which the older adults migrate, a substantial difference was observed between the preferences of older adults migrating to urban regions and those of older adults relocating to rural areas. The findings of the present study provide further insight into the decision-making of older adults regarding migration. Further, these findings constitute an empirical basis for the local governments concerned to devise and implement policies to better cope with an ageing population. [ABSTRACT FROM AUTHOR]

The rapid expansion of metro networks, e.g., in many cities of China, continuously introduces the operation of new stations every year. Due to the lack of historical data and complicate variations of short-term passenger flow in the early stage of operation, it is difficult to accurately predict inbound and outbound passenger flows of new metro stations in the short term, which would be the database for train scheduling for new stations before operation, dynamic capacity optimization for new stations under operation, short-term prediction of cycle sharing demands near new stations, and so on. Traditional methods usually failed to exactly reflect the complicate rules or were unusable without the new station's historical data. In order to solve the above problems, this paper proposes a short-term inbound and outbound passenger flow prediction model for new metro stations at the early stage of operation by combining the K-means clustering algorithm, an improved spatiotemporal long short-term memory model (Sp-LSTM), and a real-time feedback error model (mean absolute error, MAE), where passenger flows' spatial-temporal characteristics and land-use relevance are considered. The application in Guangzhou Metro, China, where Line 21 is regarded as a new line, shows that the proposed K-Sp-LSTM model has the best prediction accuracy compared with traditional methods. [ABSTRACT FROM AUTHOR]

Background and objectives: Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. Methods and data: This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. Conclusion: No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. Contribution: The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China. [ABSTRACT FROM AUTHOR]

Improving the carbon sequestration capacity (CSC) of an ecosystem by optimizing urban ecological networks is one of the effective ways to achieve the goal of "carbon neutrality" in the world. The contradiction between the irreplaceable ecological function and economic development of Yancheng City is prominent. Therefore, taking Yancheng City as an example, this paper adopted the morphological spatial pattern analysis–minimum cumulative resistance (MSPA-MCR) model to establish the ecological network of Yancheng City in 2020 and combined it with complex network theory to evaluate its ecological base, network quality, and CSC. The results show that the ecological network of Yancheng City has obvious characteristics of coastal cities. There is a significant positive correlation between CSC and the clustering efficiency of ecological sources, and improving the clustering efficiency of vegetation and water ecological nodes is conducive to enhancing the CSC of ecological networks. In terms of functional restoration of ecological networks, four types of 13 ecological stepping stones and 12 ecological corridors have been designed to strengthen the connectivity and balance of the network, and the improvement of network robustness before and after optimization verifies that the optimization scheme is reasonable and effective. This study improved the optimization method of ecological networks in Yancheng City based on enhancing the CSC of ecological nodes, which provided a theoretical framework and practical reference for the realization of global strategic goals of carbon neutrality. [ABSTRACT FROM AUTHOR]

In the current era of big data, the exponential increase in the volume of social data has exerted a significant influence on the government and all sectors of society, with the opening of government data becoming an irresistible trend. In this paper, several regional central cities are selected as the representatives of municipal governments to analyze the characteristics and weaknesses of their data-opening policies from various perspectives including policy effectiveness, policy tools, and policy targets. This is of reference significance for the municipal governments of an individual country in the formulation of data opening policies. To be specific, with 2015–2021 as the timeline, based on the six regions of the country, the central cities of each region are selected as representatives of municipal cities, and the text coding of 85 data opening policies implemented in regional central cities are performed. On this basis, a "policy tool-policy targets-policy effectiveness" collaborative measurement model is constructed through the policy tool theory, and the co-evolution analysis of the relevant policies is conducted. The research results are as follows. Firstly, there is a positive correlation between the total policy effectiveness and its quantity, indicating that the number of data-opening policies plays a positive role to a certain extent. However, the average effectiveness shows no significant increase, indicating the inadequate specificity of each policy. Secondly, the degree of synergy between policy tools fluctuates periodically, indicating that the government is constantly trying new methods, with more importance attached to the synergy between government capacity cultivation and positive incentive tools. Thirdly, policy targets continue to show new connotations over time, and there has been new progress made in the coordination between the other three objectives driven by data opening. However, it is imperative to enhance the synergy between the objectives of building a smart city and improving the services related to livelihood. Finally, some targeted suggestions are put forward on how to further improve the data opening policy implemented by municipal governments from three perspectives. [ABSTRACT FROM AUTHOR]

Large-scale and multi-annual maps of building rooftop area (BRA) are crucial for addressing policy decisions and sustainable development. In addition, as a fine-grained indicator of human activities, BRA could contribute to urban planning and energy modeling to provide benefits to human well-being. However, it is still challenging to produce a large-scale BRA due to the rather tiny sizes of individual buildings. From the viewpoint of classification methods, conventional approaches utilize high-resolution aerial images (metric or submetric resolution) to map BRA; unfortunately, high-resolution imagery is both infrequently captured and expensive to purchase, making the BRA mapping costly and inadequate over a consistent spatiotemporal scale. From the viewpoint of learning strategies, there is a nontrivial gap that persists between the limited training references and the applications over geospatial variations. Despite the difficulties, existing large-scale BRA datasets, such as those from Microsoft or Google, do not include China, and hence there are no full-coverage maps of BRA in China yet. In this paper, we first propose a deep-learning method, named the Spatio-Temporal aware Super-Resolution Segmentation framework (STSR-Seg), to achieve robust super-resolution BRA extraction from relatively low-resolution imagery over a large geographic space. Then, we produce the multi-annual China Building Rooftop Area (CBRA) dataset with 2.5 m resolution from 2016–2021 Sentinel-2 images. CBRA is the first full-coverage and multi-annual BRA dataset in China. With the designed training-sample-generation algorithms and the spatiotemporally aware learning strategies, CBRA achieves good performance with a F1 score of 62.55 % (+10.61 % compared with the previous BRA data in China) based on 250 000 testing samples in urban areas and a recall of 78.94 % based on 30 000 testing samples in rural areas. Temporal analysis shows good performance consistency over years and good agreement with other multi-annual impervious surface area datasets. STSR-Seg will enable low-cost, dynamic, and large-scale BRA mapping (https://github.com/zpl99/STSR-Seg , last access: 12 July 2023). CBRA will foster the development of BRA mapping and therefore provide basic data for sustainable research (Liu et al., 2023; 10.5281/zenodo.7500612). [ABSTRACT FROM AUTHOR]

Triggering economic growth is a requirement to promote human welfare and realize sustainable development in many developing countries. However, place-based policies' impact on economic growth is debatable, and its underlying mechanism is unknown. China's Old Revolutionary Development Program (ORDP) is a large-scale and novel type of place-based policy targeted at undeveloped regions in China. We evaluate the effect of ORDP on economic growth by employing a time-varying difference-in-differences model and further explore the potential mechanisms and heterogeneity effects. VIIRS/DNB nightlight data is used to measure economic growth. We find that ORDP can significantly promote economic growth by 4.0% and the result is still robust after several tests. Mechanism analysis shows that ORDP can improve economic growth through government intervention, industrial structure optimization, and information infrastructure construction. Heterogeneity analysis indicates that the ORDP performs better on economic growth in central Chinese cities and high-economy cities. At the same time, our paper provides three practical suggestions for stimulating economic growth in ORDP, which can be enlightening for other developing countries. [ABSTRACT FROM AUTHOR]

This paper analyzes how housing prices affect innovation and entrepreneurship. We construct a city-level panel dataset including 281 cities between 2009 and 2019 by merging housing price data from China Statistical Yearbook for Regional Economy with innovation and entrepreneurship data from Peking University Open Research Data Platform. Our results suggest that housing prices are positively associated with the vitality of innovation and entrepreneurship (VIE). The results remain consistent with a series of robustness checks. We also find that rising house prices promote VIE through the wealth effect and the siphon effect. Spatial effect analysis further shows that housing prices not only positively affect the VIE of local cities, but also positively affect the VIE of neighboring cities. These findings imply the necessity of curbing the excessive rise of housing prices and decoupling public services and benefits related to homeownership. [ABSTRACT FROM AUTHOR]

Personalized points-of-interest (POI) recommendation is very important for improving the service quality of location-based social network applications. It has become one of the most popular research directions in the industry and academia. However, the realization of high-quality personalized POI recommendation faces three major challenges: (i) the interest drift issue caused by the spatiotemporal dynamics of user check-in behavior, (ii) how to integrate as much heterogeneous information as possible to alleviate data sparseness and cold start issues, and (iii) how to use implicit feedback to model complex high-order nonlinear user-POI interactions. To jointly address all these challenges, we propose the TGVx recommendation framework and establish a dynamic personalized POI deep recommendation model, where T and G respectively represent time and geographic factors, V represents out-of-town visitors, and x represents time slot number. TGVx is composed of x parallel TGV models where the TG module mines high-order nonlinear user-POI interaction relationships and integrates multisource heterogeneous information, and the V module transfers the check-in records of out-of-town visitors in hometowns and generates pseudo check-in records in the target city. Technically, we design a new unsupervised deep learning network T-SemiDAE for the TG module. We built a POI-word heterogeneous network for the V module and used graph embedding technology to match the most similar POIs across cities and transfer check-in records. The experimental results on the actual datasets show that the TGVx model is always better than other advanced models in terms of accuracy and diversity for local and out-of-town recommendation scenarios. Compared with the best baseline model semi-deep auto-encoder with a conditional layer the average improvement rates of accuracy and diversity of TGVx are 17.1% to 58.6% and 2.25% to 28.86%, respectively. In theory, our research effectively uses data science and analysis methods to design a recommender system. In practice, our research is motivated by practical problems, and the research results have high practical promotion value. History: Accepted by Ram Ramesh, Area Editor for Data Science & Machine Learning. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71831003, 72293563, and 72172025], the Dalian Science and Technology Talent Innovation Support Policy Project [The High-level Talent Innovation Team Project 2022RG17], and the Liaoning Provincial Department of Education [Basic Scientific Research Project LJKMZ20221582]. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information (https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2023.1286) as well as from the IJOC GitHub software repository (https://github.com/INFORMSJoC/2021.0010) at (http://dx.doi.org/10.5281/zenodo.7407123). [ABSTRACT FROM AUTHOR]

Transfer between the metro (underground railway system) and buses is standard in many cities, and the simultaneous arrival of these two modes can provide passengers with a smoother transfer experience. However, previous synchronous transfer studies rarely consider different public transport modes simultaneously. This paper presents an optimization model that maximizes the number of metro and bus network synchronizations considering the connection level. An improved algorithm that combines simulated annealing (SA) and artificial bee colony (ABC) is proposed. The best nectar source position in history is combined with the SA operation. The ABC and simulated annealing and improved artificial bee colony (SA–IABC) algorithms are used to solve the model using the Nanmendou metro station and the bus stations within 1.2 km around it in Fuzhou City, China. The results show that ABC and improved SA–IABC algorithms increase the synchronization times of the metro and bus network by 17% and 24% on average, respectively, without expanding the departure frequency. [ABSTRACT FROM AUTHOR]

Urban-scale green spaces have been a central topic as of late, but community-scale green spaces are overlooked in urban studies. This paper takes community green spaces in the main urban area of Beijing as the case to quantitatively interpret the spatial-temporal patterns of their service efficiency and distribution characteristics. The measurement section of the paper includes two parts: the first part compares the applicability of two major green space service efficiency measurement methods on the community scale and determines that the Shortest Time Distance method performs better in describing the spatial-temporal patterns of service efficiency. The second part applies the Time Distance Entropy method to initially identify the locational relationship between community green spaces and neighboring residential buildings, then proposes the Green Space Distribution Coefficient method based on this relationship to analyze the 'courtyard', 'mixed', and 'centralized' distribution types alongside the transition relationships between them, and the spatial-temporal patterns of distribution characteristics are measured. The results of service efficiency reveal that the community paradigms transform from 'humanistic-oriented' to 'benefit-oriented' as the Shortest Time Distance measurement values show an ascending trend with the passage of years and the outward expansion of the ring roads. The results of distribution characteristics reveal that the community residential culture transforms from 'closeness' to 'detachment' as Green Space Distribution Coefficient measurement values show a descending trend under the same conditions. Based on the measurements, this paper further provides several optimizing strategies for community green spaces in the central urban area of Beijing. [ABSTRACT FROM AUTHOR]

Now, China has made it clear that it will strive to have CO2 emissions peak before 2030 and achieve carbon neutrality before 2060 (the "dual carbon" goals), based on the logic that carbon peaking is a prerequisite for carbon neutrality. The year 2021 is the first year of China's 14th Five-Year Plan period. As the main battlefields to achieve the "dual carbon" goals, cities are also required to build on their pathways towards such goals under new conditions. Based on the progress China has made with pilot cities for low-carbon development and the discussion on 60 cities by category, this paper identifies the commonalities and differences between Chinese cities' pathways towards carbon peaking, and concludes that Chinese cities need to peak their carbon emissions in an organized and step-wise way on the basis of classification and according to their own development level and emission characteristics. In light of the above conclusion, this paper provides feasible suggestions for Chinese cities' carbon peaking. [ABSTRACT FROM AUTHOR]

In the domain of global socio-economic dynamics, the pivotal role of food production (FP) cannot be overstated. It constitutes the bedrock of fundamental human necessities while being inexorably linked with critical aspects such as economic expansion, societal equilibrium, and geopolitical interplays. The multifaceted nature of FP appears through its direct impact on macroeconomic indicators and its latent influence on international relations and policy-making. This critical nexus underscores the imperative for a comprehensive understanding and strategic management of food production processes to sustain and enhance global socio-economic stability and growth. Investigating the nexus between green finance (GF) and FP is pivotal for ensuring national security and promoting sustainable economic development. This research thus paper examines GF's impact on FP in China as outlined in the 2017 green finance policies. It employs the difference-in-differences (DID) method and analyzes a balanced panel dataset comprising 282 cities in China from 2009 to 2020. The results show that GF has an inhibitory effect on FP, and this remains valid after a range of reliability checks, including parallel trend assessments and placebo tests. Further findings of transmission mechanism analysis indicate that non-agricultural factors and financial exclusion are critical for GF's inhibitory effect on FP. Heterogeneity analyses show that GF's inhibitory effect on FP is more pronounced in the main food-producing areas, the main food-marketing areas, and cities with better infrastructure. The empirical results of this paper comprehensively illustrate GF's impact on FP and how it contributes to the achievement of food security objectives. [ABSTRACT FROM AUTHOR]

[Display omitted] • Measure carbon emission inequalities (CEIs) of urban agglomerations under rapid urbanization. • Identify the key factors determining CEIs within the three urban agglomerations. • Account for the differences between adjacent or distant urban agglomerations. • The declining CEI is mainly due to changes in industrial structure and economic development. • CEI in the upper reaches of the YREB increases due to the changes in energy intensity. Increasing countries are articulating ambitious goals of carbon neutrality. However, large inequalities in regional emissions within a country may hinder progress toward a carbon–neutral future, as the unequal distribution of reduction responsibilities among regions could impair just transition and exacerbate uneven development, which necessitates an in-depth understanding of the mechanism of multi-scale carbon inequalities within country, region, and city. Yet, the evolution of carbon inequalities within urban agglomerations and the differences between adjacent or distant urban agglomerations have not been well understood, especially in countries undergoing rapid urbanization. Using the data of 89 cities in China's Yangtze River Economic Belt (YREB) during 2006–2021, this paper quantifies carbon emissions inequality (CEI) at different scales in a systematic regional-urban agglomeration-city hierarchical structure. Then, under the integrated mean logarithmic deviation-logarithmic mean Divisia index (MLD-LMDI) decomposition framework, multi-scale CEIs are perfectly decomposed into six interrelated drivers, i.e., industrial emission structure, energy emission intensity, industrial energy mix, energy intensity, industrial structure, and economic development. The results show that economic development, energy intensity, and industrial energy mix disparities are the main determinants accounting for CEIs at different scales. The decreasing CEI in YREB is mainly due to the changes in industrial structure and economic development, while the energy intensity effect partially hinders the mitigation of CEI. In the upper reaches of the YREB, the energy intensity effect accounts for over 94% growth of CEI during 2006–2021, while the decline in CEIs in middle and lower reaches is primarily caused by the effects of industrial energy mix and industrial structure, respectively. Further spatial decomposition analysis reveals more refined city-level heterogeneous effects and emphasizes the prioritized emission reduction direction for each city. This paper offers implications for reducing carbon inequality and insights into coordinated carbon emissions mitigation at the regional level for a carbon–neutral future. [ABSTRACT FROM AUTHOR]

Resilience is an important aim of climate adaptation in urban development planning. Since 2015, sponge city (SC) pilot construction in China has highlighted the importance of urban water systems, but has paid insufficient attention to extreme and long-term climate change risks. This paper aims to provide a new method for evaluating the urban water system climate resilience (UWSCR), classify China cities in combination with climate hazards, conduct case studies on SC pilots, and propose ways to improve the UWSCR in SCs. Firstly, Taking heavy rain and drought as hazards, an evaluation index system of UWSCR is established, including engineering resilience (ENR), ecological resilience (ECR) and evolutionary resilience (EVR). A combination model based on the analytic hierarchy process and entropy weight method is used to measure the UWSCR of 27 SC pilot cities and 253 non-pilot cities at or above the prefecture level in China. Secondly, coordinating hazard index and UWSCR index, cities are divided into four types. The results show that the ENR and EVR of SC pilots exhibited an increasing trend from 2010 to 2020 and were greater than those of non-pilots. Among the four types, Resilient Cities and Low Risk Cities with high climate resilience (CR) were mainly distributed in the eastern and central regions of China. High Risk Cities and Vulnerable Cities with low CR were mostly distributed in the central and western regions. Among the cities of high CR, SC pilots accounted for 63.0% of the pilot samples, while non-pilots only accounted for 26.5% of the non-pilot samples. Finally, this paper analyzes the typical cases of SC pilots, and puts forward some suggestions, such as considering the UWSCR systematically and holistically, improving the ECR of UWSCR, making medium-term to long-term adaptation planning and providing differentiated policy support. The originality of this work is to identify four types of cities from the perspective of UWSCR and provide reference for improving the CR of SCs. [Display omitted] • Against climate change, security risks of urban water systems have intensified. • Sponge city pilot projects in China highlighted the importance of urban water system. • The climate resilience of urban water system in China was evaluated and classified. • The proportion of high-resilience cities in the sponge city pilot sample is high. • The evaluation of urban water system climate resilience can guide sponge city constructions. [ABSTRACT FROM AUTHOR]

By taking 31 provinces (municipalities/autonomous regions) in Mainland China as the object of research, and using the data on urban population and built-up area of each region from 2005 to 2019, this paper measures the dispersion coefficient of population urbanization and land urbanization in each region through models and visually expresses the level and type of imbalance between them to reveal the temporal and spatial characteristics of imbalance. The results of the research show that since China's state-owned land was sold through bidding, auction, and listing, the overall urbanization of the population and land development have become unbalanced. There is obvious regional and category difference in imbalance between population urbanization and land urbanization. The degree of imbalance increases from the central, eastern, northeastern to western regions. The remaining 29 regions are generally lagging in population urbanization except for Beijing and Hebei province. This imbalance is mainly caused by China's dual household registration system, dual land system and the asymmetrical tax distribution system between financial rights and administrative rights. [ABSTRACT FROM AUTHOR]

As more attention is given to green and sustainable industries, an analysis of the industrial impacts on all aspects of life, including inclusive affluence, is gradually developing. Idle rural residential land is a valuable resource and an important factor in promoting sustainable development. Balanced urban and rural development contributes to inclusive prosperity, so understanding the relationship between industry and the balanced development of urban and rural can significantly impact social development. In China, achieving the balanced development requires narrowing the urban-rural income gap. This paper analyzed the impact of reallocating idle rural residential land on promoting the balanced development. The study found that industry development has a positive impact on the balanced development, with a regression coefficient of 1.478. Regions with higher industry indices in counties had better outcomes regarding the balanced development. When the development of rural industry derived from idle residential land was in good condition, the effect increased by 3.326 percentage. The results showed heterogeneity, with the regression coefficient of industry development on the balanced development in county-level cities being 0.498 larger than in urban areas. In summary, the reallocation of idle residential land can promote sustainable development, increase residents' income, and improve overall regional economic development. The results are applicable to the comprehensive reallocation of rural land resources. [ABSTRACT FROM AUTHOR]

The logistics industry and the manufacturing industry are mutually productive factors and service objects, which determines that the two must develop cooperatively. In the increasingly fierce market competition, open collaborative innovation is more conducive to improving the level of linkage between the logistics industry and the manufacturing industry, and promoting industrial development. Based on the patent data of 284 prefecture-level cities in China from 2006 to 2020, this paper uses Gis spatial analysis, spatial Dubin model and other methods to analyze the collaborative innovation between the logistics industry and manufacturing industry. The results lead to several conclusions. (i) The overall collaborative innovation level is not high, and in terms of the evolution cycle, collaborative innovation has experienced three stages: embryo, rapid development and stable development. (ii) The spatial agglomeration characteristics of the collaborative innovation between the two industries are more and more obvious, and the Yangtze River Delta urban agglomeration and the middle reaches of the Yangtze River urban agglomeration play an important role in the collaborative innovation between the two industries. (iii) The hot spots of collaborative innovation between the two industries are concentrated in the eastern and northern coastal areas, while the cold spots are concentrated in the south of the northwest and southwest areas in the late stage of the study. (iiii) The positive influencing factors of local collaborative innovation between the two industries include economic development, scientific and technological level, government behavior, and employment, while the negative influencing factors include information technology level, and logistics infrastructure. Economic development has a negative spatial spillover effect on surrounding areas, while the spatial spillover effect of scientific and technological level is significantly positive. This article aims to explore the current situation and influencing factors of collaborative innovation between the two industries, with a view to proposing countermeasures and suggestions for improving the level of collaborative innovation between the two industries, and also providing new ideas for research on cross industry collaborative innovation. [ABSTRACT FROM AUTHOR]

This study provides a viable path to save energy by means of e-commerce development. Taking the national e-commerce demonstration cities (NEDC) pilots policy implemented in China as a quasi-natural experiment, based on the city panel data from 2006 to 2019, this study applies the multi-period difference-in-difference (DID) method to evaluate the effect of NEDC on energy saving in pilot cities. The empirical results suggest that the NEDC policy obviously contributes to energy conservation. The treated cities reduced energy consumption by 14.2% as a result of the implementation of NEDC, relative to the untreated cities. The conclusions remain valid after conducting robustness tests such as placebo test, instrumental variables regression, propensity score matching-difference-in-difference (PSM-DID), and synthetic difference-in-difference (SDID). The NEDC achieves energy-saving effects through technological innovation, industrial restructuring, and economic agglomeration. Furthermore, the heterogeneity analysis indicates that, in cities with high levels of human capital, well-developed information infrastructure, non-resource-based cities, and favorable business environments, the impact of NEDC on energy saving is more significant. Analysis of spatial effects shows that the implementation of NEDC has negative externalities, increasing energy consumption in the surrounding area. In the context of the digital economy, this paper presents new insights on the relationship between e-commerce and energy consumption and provides policy direction for countries looking for energy-saving solutions. [ABSTRACT FROM AUTHOR]

The Local Climate Zone (LCZ) classification scheme is a vital method of building a category dataset for high-resolution urban land. For the development of urban meteorology, air pollution and related disciplines, the high-resolution classification data of urban buildings are very important. This study aims to create LCZ datasets with detailed architectural characteristics for major cities and urban agglomerations in China, and obtain more accurate results. We constructed 120 m resolution land use datasets for 63 cities (mainly provincial capitals, municipalities directly under the Central Government, important prefecture-level cities and special administrative regions) and 4 urban agglomerations in China based on the local climate zone (LCZ) classification scheme using the World Urban Database and Access Portal Tools method (WUDAPT). Nearly 100,000 samples were used, of which 76,000 training samples were used to provide spectral signatures and 23,000 validation samples were used to ensure accuracy assessments. Compared with similar studies, the LCZ datasets in this paper were generally of good quality, with an overall accuracy of 71–93% (mean 82%), an accuracy for built classifications of 57–83% (mean 72%), and an accuracy for natural classifications of 70–99% (mean 90%). In addition, 35% of 63 Chinese cities have construction areas of more than 5%, and the plateaus northwest of Chengdu and Chongqing are covered with snow all year round. Therefore, based on the original LCZ classification system, the construction area (LZC H) and the snow cover (LCZ I) were newly added as the basic classifications of urban LCZ classification in China. Detailed architectural features of cities and urban agglomerations in China are provided by the LCZ datasets in this study. It can be applied to fine numerical models of the meteorological and atmospheric environment and improve the prediction accuracy. [ABSTRACT FROM AUTHOR]

While rapid urbanization promotes social and economic development, it exacerbates human outdoor thermal comfort, which increases the risks to human health. This paper uses four thermal comfort indices and multiple satellite observations to explore the urbanization effect on summer heat stress in Guangdong from 1979–2018, a coastal province of China. Two types of thermal comfort index are used here, namely the direct thermal comfort index (Heat Index, HI; Temperature–Humidity Index, THI; Discomfort Index, DI) and the physiological thermal comfort index (Universal Thermal Climate Index, UTCI). We compare the differences in the urbanization effects on the changes in the three direct thermal comfort indices (HI, THI, and DI) and a physiological thermal comfort index (UTCI). The results show that all four thermal comfort indices indicate an overall warming trend. Of them, urban sites show a higher warming trend than rural sites, indicating that heat stress changes are significantly influenced by urbanization from 1979–2018, which is consistent with the effect of urbanization on surface air temperature. However, except for the UTCI, this warming of direct thermal comfort indices affected by urbanization has become insignificant under the regional vegetation greening from 2004–2018 (also consistent with surface air temperature). This is primarily attributed to the different effects of wind speed on the physiological thermal comfort index in urban and rural areas: Decreasing wind speeds in urban areas lead to an increase in UTCI, while wind speeds in rural areas increase instead and decrease UTCI, thus widening the UTCI differences between urban and rural areas. Our results indicate that urbanization has a different effect on thermal comfort indices. When using the thermal comfort index, it is necessary to consider that different thermal comfort indices may bring different results. UTCI considers more factors that affect human heat perception, so it can better describe human outdoor thermal comfort. It also highlights the importance of urban ventilation and urban greenness in mitigating urban outdoor thermal comfort in the sustainable construction of future urbanization in coastal cities. [ABSTRACT FROM AUTHOR]

It is very common that taxi is used as a feeder mode to/from a metro station especially in third-tier cities of China. But research on taxi-metro integrated use is rather limited. This paper investigates the relationship between feeder-related built environment and taxi-metro integrated use by using taxi trajectory data in Lanzhou, China. Firstly, regression models are developed to explore the transfer distance of access/egress trips during peak hours. Then, the catchment area is delineated for collecting feeder-related environment variables. Finally, several negative binomial regressions are employed to examine the relationships between feeder-related built environment and taxi-metro integrated use during peak hours on weekdays. The results reveal that (a) people prefer to use taxi as feeder mode for metro access during morning peak hours and for metro egress during evening peak hours; (b) the transfer distance of taxi-metro integrated use is about 3.8 km; (c) higher mixed land use generates more taxi-metro integrated use during evening peak hours. Higher proportion of residential land use attracts more taxi-metro integrated use for metro access during morning peak hours. Those findings will help transport planners to develop tailored land-use interventions to improve transit accessibility and promote the sustainable multimodal travel. [ABSTRACT FROM AUTHOR]

High-rise building areas (HRBs) provide significant social and environmental services and play a crucial role in modern urbanization. The large-scale and long-term spatial distribution of HRBs is of great interest to many fields, such as urban planning and local climate analysis. While previous studies have confirmed the value of Sentinel-2 images in extracting HRBs and their changes, current work is limited to relatively local areas and short-term analysis. One reason is due to the fact that the earliest Sentinel-2 image can only date back to 2015. To address this research gap, this paper proposes an efficient procedure to intelligently extract HRBs and their changes from multitemporal Landsat-7 and Sentinel-2 images, using a specifically designed fully convolutional network. To validate the proposed method, we selected four typical cities in China, namely, Beijing, Shanghai, Guangzhou, and Zhengzhou, as study areas. We utilized Landsat-7 images acquired in 2000 and 2010, along with Sentinel-2 images acquired in 2020, as experimental data. We extracted and analyzed three periods of HRBs and their changes in the four cities, along with urban rail terminal data and gross domestic product (GDP) data in the same period. The results show that the proposed method can efficiently extract HRBs and their changes in the four cities over the past 20 years, with an overall accuracy of more than 90%. HRBs changes are primarily driven by urban planning policies and geographical factors. There is a strong positive correlation between the increase in HRBs and the increase in rail terminals, both in terms of quantity and spatial distribution. Additionally, there is a positive correlation between HRBs increase and GDP increase in terms of quantity, but the trend varies in different cities due to their diverse developing modes. Overall, the results indicate that the proposed method can be a potential operational tool to extract large-scale and long-term HRBs and their changes in China. [ABSTRACT FROM AUTHOR]

Car use restrictions have been adopted in some mega cities that experience rapid car ownership increase and worsening traffic congestion. Although easy to implement and considered fair, most implementations of this travel demand management policy do not offer travelers the flexibility to choose the days that they cannot use their cars. In this paper, we study a flexible car use restriction policy under which a private car cannot be driven on a certain day of a week, but the day can be chosen by its owner. Under this flexible policy, individuals face a dilemma between driving in congestion and traveling without a car, each incurring a cost of its own. The resulting equilibrium solutions under these two competing choices were derived, and a series of laboratory experiments were carried out to validate the theoretical results. The experimental results are found to be in agreement with the theoretical results. Moreover, our analysis shows that the flexible car use restriction policy reduces the average travel cost with a lesser increase in average driving cost when compared with the traditional car use restriction policy. Funding: Z.-Y. Gao was supported by the National Natural Science Foundation of China [Grant 71621001]. W.-X. Wang was supported by the National Natural Science Foundation of China [Grant 71631002]. R. Jiang was supported by the National Natural Science Foundation of China [Grant 71931002]. X.-Y. Sun was supported by the National Natural Science Foundation of China [Grant 71961002]. B.-Y. Zhang was supported by the National Natural Science Foundation of China [Grants 71922004 and 72131003]. X. Han was supported by the National Natural Science Foundation of China [Grant 71801011] and by the China Postdoctoral Science Foundation [Grant 2018M631331]. Supplemental Material: The e-companion is available at https://doi.org/10.1287/trsc.2023.1200. [ABSTRACT FROM AUTHOR]

Identifying the relationship between carbon neutrality initiatives and its economic impact is crucial in evaluating the cost of low-carbon transition for policy makers. In this paper, a theoretical model is built to discuss the effects of the low-carbon pilot policy in China on urban economic resilience and an empirical test is conducted to examine the relationship using the Heckman two stage model and a panel data of 277 cities from 2004 to 2020. The results show that low-carbon pilot policy significantly enhanced urban economic resilience and the stimulating effect is mainly achieved by motivating technology innovations. In addition, further analysis indicates that low-carbon pilot policy has a more pronounced effect on improving urban economic resilience of cities in the central and western regions than eastern regions. The effect is also more prominent in non-first-tier cities than first-tier cities. The results are robust to placebo test, the Propensity Score Matching Difference-in-Difference test and the test for alternative measure of urban economic resilience. The findings show that the low-carbon pilot policy is consistent with the goal of improving urban economic resilience and technology innovation is the essential pillar of sustainable development. [ABSTRACT FROM AUTHOR]

Urbanization drives the concentration of innovation elements and knowledge diffusion, which is conducive to enhancing regional innovation capacity. To meet the developmental needs of the new era, China has released the National New Urbanization Plan (2014–2020) to test the effect of this policy on urban innovation. The 2014 comprehensive pilot project of China's new urbanization strategy is considered a quasi-natural experiment. This study examines relevant data from cities at the prefecture level and above from 2008 to 2019 using DID, PSM-DID, intermediary effect, and other methods. We established an empirical model to investigate the impact of new urbanization pilot policies on urban innovation. The results indicate that the new urbanization pilot policy can significantly promote an increase in urban innovation capacity. The heterogeneity of the impact of new urbanization pilot policies is evident in the improvements to urban grade, region, scale, etc. Regarding function mechanism, new urbanization can promote urban innovation through talent gathering, industrial gathering, income scale, and other effects. This paper posits the importance of summarizing the success of the pilot project of new urbanization and explores new urbanization to promote urban innovation from multiple perspectives. We put forth recommendations based on the experience of different cities to implement an urban innovation differentiation strategy in constructing new urbanization. [ABSTRACT FROM AUTHOR]

The natatorium's ventilation problem receives much concern because of its large wet load. The outdoor humidity ratio in transition season is the basic design parameter of the ventilation calculation, directly affecting the rationality of architectural design. At present, the ventilation-curve (V-C) method is the most widely used method to determine the outdoor humidity ratio in the transition season in China. However, due to failing to reflect non-guaranteed hours, the rationality of this value is difficult to assess by employing this approach. This paper presents a new method, the typical transition season method (TTS), for determining the outdoor humidity ratio in the transition season of a natatorium. The TTS method selects the transition season based on the typical meteorological year (TMY) data and calculates the outdoor humidity ratio with multiple non-guaranteed hours. This can well-represent the local perennial climate characteristics and clearly reflect the non-guaranteed hours. In this study, through selecting six typical representative cities in China, the evaluation of the outdoor humidity ratio is achieved through calculating ventilation volume and air change rate, verifying the rationality of this method. The results show that the humidity ratio obtained by the V-C method is lower than that obtained by the TTS method at about 2 g/kg without guarantee of 200 h humidity ratio, and even that the maximum difference is 6.64 g/kg. Meanwhile, the validation results of the ventilation calculation show that the humidity ratio determined by the V-C method cannot meet the minimum design requirements in five cities, while the humidity ratio obtained by the TTS method cannot meet the requirements in only one city. [ABSTRACT FROM AUTHOR]

With extreme rainfall events and rapid urbanization, urban flood disaster events are increasing dramatically. As a key flood control city in China, Changchun City suffers casualties and economic losses every year due to floods. The improvement of flood resilience has become an important means for cities to resist flood risks. Therefore, this paper constructs an assessment model of urban flood resilience from four aspects: infrastructure, environment, society and economy. Then, it quantifies infrastructure and environmental vulnerability based on GIS, and uses TOPSIS to quantify social and economic recoverability. Finally, based on k-means clustering of infrastructure and environmental vulnerability and social and economic recoverability, the flood resilience of Changchun City was evaluated. The results show that different factors have different effects on flood resilience, and cities with low infrastructure and environmental vulnerability and high socioeconomic recoverability are more resilient in the face of floods. In addition, cities in the same cluster have the same flood resilience characteristics. The proposed framework can be extended to other regions of China or different countries by simply modifying the indicator system according to different regions, providing experience for regional flood mitigation and improving flood resilience. [ABSTRACT FROM AUTHOR]

• Digitalization become a new driving force to improve energy-saving and emission reduction performance (EEP). • The relationship between digitalization and EEP has spatial and temporal heterogeneity. • There is a synergy between digitalization and industrialization. • Some constructive policy suggestions are proposed from the perspective of digital development. In the digital era, enterprises actively use digital technology to enable resource conservation and pollution reduction, which has important practical significance. However, the existing research has not fully clarified the link between digitalization and energy-saving and emission reduction. This paper measures the digital development level and energy-saving and emission reduction performance (EEP) of 271 Chinese cities from 2003 to 2019 and empirically explores the impact of digitalization on EEP. The empirical results are: (1) digitalization can significantly improve EEP in Chinese cities, and become a new driving force to save energy and reduce emissions in the new era. After solving the endogeneity problems and replacing the explained variables, the conclusion remains robust. (2) The relationship between digitalization and EEP has significant spatiotemporal heterogeneity. Digitalization helps to promote EEP in China's eastern cities, but it has not shown a positive effect in western cities. The positive effect of digitalization began to emerge after 2011. (3) There is a synergy between digitalization and industrialization, which enables cities to save energy and reduce emissions. This study helps clarify the relationship between digitalization and EEP, which provides important insights into how digitalization can empower cities' energy-saving and emission reduction. [ABSTRACT FROM AUTHOR]

In this paper, the adoption of SO2 emission tax rates higher than the legal minimum standard is regarded as a noteworthy policy reform in China (quasi-natural experiment), and a spatial Difference-in-Differences (Spatial-DID) model is constructed to test the direct effects (local effects) and indirect effects (spatial spillover effects) of SO2 emission tax policy reform on PM2.5 concentrations in the atmosphere of 285 China's cities. The estimation and calculation results of the Spatial-DID model show that the SO2 emission tax policy reform can significantly reduce local PM2.5 concentration and significantly promote PM2.5 concentration in surrounding areas. The results of heterogeneity analysis show that the SO2 emission tax policy reform can produce a relatively more beneficial spatial spillover effect in eastern cities and higher administrative level cities, while the pollutants emission rights trading and the reform of NOx emission tax rates can produce beneficial spatial spillover effects when cooperating with the reform of SO2 emission tax rates. The results of the mediation effect analysis show that the higher SO2 emission tax rate can aggravate the surrounding PM2.5 pollution by promoting the aggregation level of industrial production factors and the industrial SO2 emission intensity in the surrounding areas, which can support the existence of the pollution heaven effect. [ABSTRACT FROM AUTHOR]

Because well-being and energy efficiency are both important issues in building, there is an increase need for comfort and energy saving. Some critical factors affecting them are still not clear. This paper firstly investigated the influence of the orientation of the window on indoor daylight glare. Secondly, the influence of longitude and latitude on indoor daylight glare, and the distribution of daylight glare in China by using K-Nearest Neighbor algorithm (KNN algorithm) were studied. Daylight Glare Probability (DGP) was used as glare evaluation index in the study. The results show that daylight glare is the most serious in the west and south, then in the east and the least in the north for the window of the room in different orientations. The glare gradually increases with the increase of the latitude of the cities at the same longitude. The effect of the longitude of the cities at the same latitude on glare has no specific linear relationship. We also get the glare situation of cities without meteorological files by investigating the distribution of daylight glare in China. [ABSTRACT FROM AUTHOR]

The trend of market-oriented land transaction scheme and the optimal allocation of land resources have become two important components of ecological sustainable development. However, the relevance of analyzing effects of land marketization on ecological and environmental development cannot be overemphasized. The ecological and environmental effects of land marketization are the focus of this paper. We begin by developing a theoretical framework to investigate how land marketization affects eco-efficiency. Moreover, we develop a data envelopment analysis model to measure eco-efficiency. We empirically investigate the effect of land marketization on eco-efficiency using a data set of 251 cities in China over the period of 2003 to 2018. Both theoretical and empirical results show that the land marketization exerts positive effects on eco-efficiency. Specifically, a 100% increase in land marketization level leads to a 2.4 percent increase in eco-efficiency. The heterogeneous effects and spatial effects of the land marketization on eco-efficiency are also examined. Besides, the endogeneity issues are also discussed using instrumental variable approach. Finally, the mechanism analysis shows that land marketization improves eco-efficiency primarily through improving efficiency change, best practice change and technology gap change, respectively. The main conclusions are confirmed by several robustness checks. [ABSTRACT FROM AUTHOR]

Large-scale and multi-annual maps of building rooftop area (BRA) are crucial for addressing policy decisions and sustainable development. In addition, as a fine-grained indicator of human activities, BRA could contribute to urban planning and energy modelling to provide benefits to human well-being. However, it is still challenging to produce large-scale BRA due to the rather tiny size of individual buildings. From the viewpoint of classification methods, conventional approaches utilize high-resolution aerial images (metric or sub-metric resolution) to map BRA; unfortunately, high-resolution imagery is both infrequently captured and expensive to purchase, making the BRA mapping costly and inadequate over a consistent spatio-temporal scale. From the viewpoint of learning strategies, there is a non-trivial gap that persists between the limited training references and the applications over geospatial variations. Despite the difficulties, existing large-scale BRA datasets, such as those from Microsoft or Google, do not include China, hence there are no full-coverage maps of BRA in China yet. In this paper, we first propose a deep-learning method, named Spatio-Temporal aware Super-Resolution Segmentation framework (STSR-Seg) to achieve robust super-resolution BRA extraction from relatively low-resolution imagery over a large geographic space. Then, we produce the multi-annual China building rooftop area dataset (CBRA) with 2.5 m resolution from 2016-2021 Sentinel-2 images. The CBRA is the first full-coverage and multi-annual BRA data in China. With the designed training sample generation algorithms and the spatio-temporal aware learning strategies, the CBRA achieves good performance with the F1 score of 62.55% (+10.61% compared with the previous BRA data in China) based on 250,000 testing samples in urban areas, and the recall of 78.94% based on 30,000 testing samples in rural areas. Temporal analysis shows good performance consistency over years and the well agreement to other multi-annual impervious surface area datasets. The STSRSeg will enable low-cost, dynamic and large-scale BRA mapping (https://github.com/zpl99/STSR-Seg). The CBRA will foster the development of BRA mapping and therefore provide basic data for sustainable research (Liu et al., 2023; https://doi.org/10.5281/zenodo.7500612). [ABSTRACT FROM AUTHOR]

In China, rapid urbanization and the decline of the canal's shipping function have directly led to the decline of the space and style of ancient towns with canals. The ancient town of Xixing, known to be the first canal town, is located west of the Zhedong canal section of the Grand Canal. It used to be the most active transportation hub and trade transit point in the east Zhejiang Province. However, the canal is now facing problems in protection and renewal, which require urgent attention. For example, the streets of the ancient town are separated from the water system space, the self-organizing and development ability of the ancient town has weakened, and the spatial vitality is scarce. Firstly, by comparing and analyzing whether the canal is used as a road network under two different spatial scales, the area with the highest degree of spatial integration is obtained before judging whether the canal has an important influence and control on the street spaces of the ancient town. Secondly, as the canal is no longer used as a transportation network nowadays, the internal spatial structure characteristics of streets and alleys are analyzed. Finally, the topological structure analysis is carried out in the 3 km area from the border of the planning control area, and the integrated development of the ancient town space and urban transportation network is then discussed. Further, the vitality renewal strategies of the ancient town under different spatial scales are put forward to provide the empirical basis and decision-making reference for the better sustainable development of ancient towns with canals. According to research, once the ancient town is considered on a larger urban scale, the areas with the best integration and accessibility, like the water-adjoined spaces change to intersection spaces and urban road network areas. Consequently, in order to realize the sustainable development of Xixing ancient town, the city system must overcome its shortfalls in operation. The methods and conclusions in the paper can effectively contribute to the development of the ancient town. The research significantly helps to improve the average land sharing, commercial distribution, and public facilities layout in the practice of protection and development in ancient towns and provides an empirical basis and decision-making references for relevant management departments. [ABSTRACT FROM AUTHOR]

Exploring the driving factors behind urban polycentricity is of paramount significance for advancing the implementation of urban polycentric strategies. In this, paper takes 41 cities in the China's Yangtze River Delta region are taken as the research objects, and the degree of urban polycentricity is measured using non-parametric and social network methods. Then, the geographic probe method is applied to reveal the driving factors of the spatial differentiation of urban polycentricity. The research results showed that (1) the distribution of hot and cold spots of the urban polycentricity index was roughly the same between 2006 and 2015, while and the distribution of hot and cold spots of the urban polycentricity index varied greatly between 2015 and 2020. (2) In 2010, the proportions of the secondary and industry tertiary industries and the topographic relief were the main driving factors of urban polycentricity. By 2020, the population size and topographic relief were the key drivers of urban polycentricity. [ABSTRACT FROM AUTHOR]

Environmental protection and sustainable development are now profoundly ingrained in the public consciousness in the modern era of the global green revolution. First, this paper uses an evolutionary game model to theoretically analyse the impact of environmental regulation and green finance on enterprises by dissecting the game behaviour between local governments, banks and enterprises. Then, we incorporate entrepreneurial spirit into the model to determine whether entrepreneurial spirit accelerates the achievement of green sustainability objectives. Environmental regulation and green finance are found to contribute substantially to the innovation of green technologies by local enterprises, while entrepreneurial spirit accelerates this process. Finally, we empirically test the findings based on a prefecture-level panel dataset from 2007 to 2020. We find that green finance has a positive impact in Central and Western cities of China, while Eastern cities are in greater need for government environmental regulation controls. For entrepreneurial spirit, the incentive effect of entrepreneurial spirit on the level of green technology innovation is more significant in Central and Western regions of China. This paper enriches the field of research on entrepreneurial spirit and regional green sustainable development by providing empirical evidence for the evaluation of environmental regulatory and green financing policy impacts. [ABSTRACT FROM AUTHOR]

High carbon emissions and population aging are two obstacles to China's development as an emerging economy. It is urgent to scientifically examine the impacts of population aging on carbon emissions to discover new pathways for urban carbon emission reduction. However, existing studies face challenges in terms of focusing on and methodology for accurately capturing the role of industrial production and energy consumption in the environmental effects of population aging. This paper constructs a chain mediation analytical framework and systematically examines the intrinsic linkages between population aging and carbon emissions in Chinese cities from 2000 to 2020 using a two-way fixed effects model. This paper has three main findings. (1) The positive correlation between urban population aging and carbon emissions development is generally low, with coupling coordination degree values of 0.4233, 0.4458, 0.4220, 0.4715, and 0.4665 for each yearly cross-section. (2) For every 1% increase in the population aging rate, carbon emissions decrease by 0.3478% on average. The carbon reduction effect of population aging is significantly greater in low-emissions cities and high-income cities than in other cities. (3) The industrial upgrading (IU) path, energy conservation (EC) path and chain mediation (CM) path account for 72.43%, 7.23% and 20.34%, respectively, of the indirect effects. If the causal link between IU and EC is not considered, the EC effect will be overestimated by 281.16%. The results of the study suggest that properly coping with population aging and reducing carbon emissions are not completely opposed to each other, a conclusion that passes both endogeneity exclusion and robustness check. This paper advocates replacing the one-size-fits-all approach in carbon emissions management and investing more in policy preferences to support carbon emission reduction in both high-emissions and low-income cities. [Display omitted] •The synergistic trends of carbon emissions and population aging are not apparent. •Population aging significantly reduces carbon emissions at the city scale. •Linkage effect of industrial upgrading and energy conservation on carbon emission reduction. •Energy conservation effect of population aging amplified by industrial upgrading. [ABSTRACT FROM AUTHOR]

Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy". [Display omitted] • The staggered differences-in-differences method is employed to examine the direct and spatial spillover effects of NEPC on cities' GEE in China. • This paper uses NEPC as a quasi-experiment for digital transformation. • NEPC significantly improves green economic efficiency by 2.6%. • Green structural transformation, innovation, and environmental concerns are main channels. • Positive spillover effect of NEPC on green economy efficiency in non-pilot cities. [ABSTRACT FROM AUTHOR]

This paper explores how green fiscal expenditure affects G reen T otal F actor E nergy E fficiency (GTFEE) from both non-spatial and spatial perspectives based on selected panel data of 254 cities in China. The results of the non-spatial panel model indicate that green fiscal expenditure has a significant positive impact on GTFEE. A comparative study of different econometric models shows that the main parts of the results are largely consistent, which indicates that the conclusions are robust. The spatial autocorrelation findings indicate a statistically significant presence of positive spatial spillover effects in the GTFEE of Chinese cities. Spatial Durbin Model (SDM) and Dynamic Spatial Durbin Model (DSDM) indicate that green fiscal expenditure has a similarly significant positive effect on GTFEE, which will increase over time. This paper considers different spatial weight matrices and changing measures to measure GTFEE, and the conclusions remain robust. Furthermore, industrial structure upgrading, and digital economy are vital in strengthening the relationship between local governments' green fiscal expenditure and GTFEE. According to heterogeneity analysis, green fiscal expenditure has a more significant effect on the GTFEE in mature resource-based cities and non-resource-based cities. • Influence factors of green total factor energy efficiency (GTFEE) is explored. • Green fiscal expenditure (GFE) has a significant positive impact on GTFEE. • Significant positive spatial spillover effects exist in the GTFEE of Chinese cities. • Industrial structure upgrading and digital economy are vital for GFE and GTFEE. [ABSTRACT FROM AUTHOR]

Background: The purpose of this paper is to study how the Delta variant spread in a China city, and to what extent the non-pharmaceutical prevention measures of local government be effective by reviewing the contact network of COVID-19 cases in Xi'an, China. Methods: We organize the case reports of the Shaanxi Health Commission into a database by text coding and convert them into a network matrix. Then we construct a dynamic contact network for the corresponding analysis and calculate network indicators. we analyze the cases' dynamic contact network structure and intervals between diagnosis time and isolation time by using data visualization, network analysis method, and Ordinary Least Square (OLS) regression. Results: The contact network for this outbreak in Xi'an is very sparse, with a density of less than 0.0001. The contact network is a scale-free network. The average degree centrality is 0.741 and the average PageRank score is 0.0005. The network generated from a single source of infection contains 1371 components. We construct three variables of intervals and analyze the trend of intervals during the outbreak. The mean interval (interval 1) between case diagnosis time and isolation time is − 3.9 days. The mean of the interval (interval 2) between the infector's diagnosis time and the infectee's diagnosis time is 4.2 days. The mean of the interval (interval 3) between infector isolation time and infectee isolation time is 2.9 days. Among the three intervals, only interval 1 has a significant positive correlation with degree centrality. Conclusions: By integrating COVID-19 case reports of a Chinese city, we construct a contact network to analyze the dispersion of the outbreak. The network is a scale-free network with multiple hidden pathways that are not detected. The intervals of patients in this outbreak decreased compared to the beginning of the outbreak in 2020. City lockdown has a significant effect on the intervals that can affect patients' network centrality. Our study highlights the value of case report text. By linking different reports, we can quickly analyze the spread of the epidemic in an urban area. [ABSTRACT FROM AUTHOR]

The impact of Chinese-style fiscal decentralization on regional energy intensity has long been disputed by the supporters of "federal environmentalism" and those who hold "race to the bottom" views. At the same time, with the transformation of China's development mode, the Chinese government is paying increasing attention to the protection of ecological civilization and the realization of sustainable development, and the government's attention to the ecological environment is becoming an important factor affecting regional energy intensity. Therefore, this paper takes the fiscal decentralization and ecological attention of local governments in China as the research object and analyzes their impact mechanism on regional energy intensity. Firstly, the entropy weight method was used to measure the comprehensive score of fiscal decentralization of Chinese local governments, and the text analysis method was used to obtain the ecological attention index of Chinese provincial local governments, which was sorted into panel data of 30 provinces (municipalities and autonomous regions) in mainland China from 2007 to 2019. The spatial econometric model and panel threshold model are structured as the means for analyzing the impact that fiscal decentralization and the ecological attention of local governments have, respectively, on regional energy intensity targets. We obtained the following conclusions: Chinese fiscal decentralization can significantly improve the regional energy intensity, and the fiscal decentralization of a region can significantly reduce the energy intensity in nearby regions; the enhancement of ecological attention of local governments will significantly inhibit regional energy intensity, and also has a significant inhibitory effect on the energy intensity of neighboring regions. As the threshold variable—which is the ecological attention of local governments—increases and reaches a certain level, fiscal decentralization will significantly and reversely inhibit regional energy intensity, indicating that the ecological attention of local governments can moderate the distortion of fiscal decentralization with regards to regional energy efficiency. [ABSTRACT FROM AUTHOR]

With the progress of the industrial revolution and the development of modern science and technology, China's urbanization process has been promoted. Urban and rural economic and social construction has greatly improved the local appearance and social structure. Human activities and natural ecology have affected the whole geological-ecological process, further aggravated the geological-ecological damage, and caused more serious geological disasters, especially in some places (especially in mountainous areas). In recent years, strong geological disasters have occurred in Wenchuan, Yushu, and Lushan regions of China, which not only seriously endanger the life safety and social life of the affected people, but also damage the geological-ecological structure and social functions of the region, especially in the geographically sensitive Alpine urban areas. It also produced many secondary disasters, such as landslides and land collapses. Mountainous cities and towns have special requirements for construction land, which is difficult to construct. Industrial land resources are in short supply, urban and rural comprehensive construction land is not active, and cultivated land area resources are tight. Compared with plain towns with superior geological conditions, mountain towns are more vulnerable to adverse geological environment such as geological ecology, landform, ecological vegetation, and hydrology. The geographical natural environment, as an organic whole that combines and interacts with the geomorphic natural environment, the biological-ecological environment, and the human social management environment, is the main reason that affects the development of mountain towns. Once the mountain geological ecology is destroyed, a series of geological disasters will often be induced, which will seriously restrict the healthy development of mountain towns. Scientific management of the geological environment plays an important role in the assessment of the geological environment restoration of mountain towns after disasters. Therefore, taking the most beautiful counties in China, Baoxing City, and Tianquan County as examples, on the basis of studying the complex geological-ecological theory of geological disasters, this paper further improves the traditional ecological footprint model in China, and using the interval direct fuzzy information constructs the metric index of ecological restoration scheme of mountain towns, and determines the evaluation index and optimal scheme of ecological restoration. From the aspects of landscape layout construction, disaster prevention and mitigation planning and improvement, and environmental restoration project, the future geoecological restoration and response strategy of Lushan County are pointed out, which provide guidance for the postdisaster geoecological safety layout construction. [ABSTRACT FROM AUTHOR]