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The aim of this paper is to explore whether and how urban road transport (URT) development affects haze pollution. One of the innovations of this paper is that URT development is measured by road accessibility with novel digital elevation model datasets, which have been used by few scholars. The endogenous problem caused by revere causality issue in the relationship between URT development and haze pollution is also considered. Based on the panel data of prefecture-level cities of Yangtze River Delta (YRD) region in China from 2011 to 2018, this paper uses long-lagged values of URT development as the instrumental variable, employing the two-stage least squares (2SLS) method. The study shows that URT development leads to an increase of haze pollution. Moreover, mechanism tests based on moderating and mediating models support the finding that decreasing haze pollution resulted from better connection effects, while rising agglomeration effects tend to bring about increasing haze pollution, and the latter effect is larger in magnitude than the former. Current URT development may have long-term negative consequences for livability of YRD cities, and urban decision makers should reconsider the effectiveness of the current road transport investment and construction. [ABSTRACT FROM AUTHOR]

Comparing with cities, rural communities especially those declining rural communities have become vulnerable to natural disasters owing to their backward socioeconomic conditions. Taking Xun County of China's Henan Province as the study area, the paper aims to evaluate rural community resilience to flood by unveiling the connection between individuals' cognition, follow-up actions and the community resilience. Research results show that: (1) The logic chain exists as individual's cognition to disaster leads to their constructive actions to cope with disaster, which contribute to community resilience. (2) At the cognition dimension, individual's knowledge reserve of disaster prevention and their recognition to local authority are playing an important role in their decision making and follow-up behaviors when disaster occurs. (3) At the action dimension, individual's familiarity with the disaster preparedness, efficient information transmission when disaster occurs and villagers' following order and their unity of action all contribute to community resilience to disaster. The paper proposes ways to improve rural community resilience to disasters based on the research findings. [ABSTRACT FROM AUTHOR]

In the process of global urban development, there are urgent ecological security and environmental pollution problems, green development is the fundamental way for urban sustainable development, economic transformation and mitigation of ecological and environmental problems. Based on the panel data of 283 cities at prefecture level and above in China from 2003 to 2017, this paper analyzes spatial–temporal evolution characteristics of urban green development efficiency (UGDE) and the peer effects of UGDE between cities of different grades. It is found that during the study period, in terms of temporal evolution, the average UGDE in China increased from 0.47 in 2003 to 0.61 in 2017, with a cumulative growth rate of 29.79%, showing a rising trend in general. In terms of spatial evolution, the number of low-efficiency cities and medium-efficiency cities continued to decrease. The eastern region has always been the main distribution area of higher-efficiency cities and high-efficiency cities; in the central region, UGDE in most cities improved significantly; in the western region, UGDE has always lagged behind that in the eastern and central regions. In addition, the center of gravity of UGDE presented a trend of northwest migration in general, with a total displacement of 100.07 km, and UGDE showed a spatial dispersion trend. The empirical results indicate that the improvement of UGDE in large cities has a driving effect on that in neighboring medium cities and small cities through the positive peer effect, and the growth of UGDE in medium cities has a promoting effect on that in neighboring small cities through the positive peer effect; the increase of UGDE in medium cities has a positive peer effect on that in neighboring large cities, and the growth of UGDE in small cities has a positive peer effect on that in neighboring medium cities; UGDE promotes each other between large cities through the positive peer effect. [ABSTRACT FROM AUTHOR]

Green finance (GF) is recognized as a key driver of sustainable development. While existing studies have extensively discussed the relationship between GF and the Sustainable Development Goals (SDGs), few have explored the coupling coordination relationship between GF and SDGs. In this paper, we use data from thirty Chinese provinces (municipalities and autonomous regions) from 2008–2021 to examine the degree of coupling coordination development (CCD) between GF and the SDGs systems using the CCD model. We find that most SDGs and their sub-goals exhibit a significant upward trend, except for SDG8, 14–16. GF presents a fluctuating upward trend, with a significant decline in 2010 and 2019. The CCDs between GF and SDGs and their sub-goals generally show an M-shaped upward trend in most regions, with most of them experiencing a synchronous decline in 2011–2012 and 2019. In the analysis of regional heterogeneity, the eastern region performs better in SDG8–9, the central region performs better in SDG3, 14–15, while the western region performs better in SDG7. This paper provides empirical evidence for a further in-depth understanding of the relationship between GF and SDGs, which can contribute to advancing GF development and the SDG process. [ABSTRACT FROM AUTHOR]

Improving total factor carbon emission efficiency (TCE) is the key to achieving carbon emission reduction targets while ensuring economic growth. In this paper, the global Malmquist index based on the SBM model is used to measure TCE of 283 cities in China from 2011 to 2019. On this basis, this paper uses the spatial econometric model and intermediary effect model to empirically analyze the impact of industrial co-agglomeration on TCE and its transmission mechanism. Furthermore, considering the differences in geographical location and resource endowment among regions, this paper analyzes the heterogeneous effect of industrial collaboration agglomeration on TCE in different regions and cities. The results show that: (1) Industrial co-agglomeration can improve TCE, and its main transmission channel is technological innovation. (2) Industrial co-agglomeration has a positive spatial spillover effect. Industrial co-agglomeration in one region can improve the TCE in the surrounding regions. (3) Industrial co-agglomeration of cities with different geographic locations and resource endowments has a heterogeneous effect on TCE. Regarding geographical heterogeneity, the industrial co-agglomeration in the eastern region has the greatest promoting effect on TCE, followed by the central region. However, the impact of industrial co-agglomeration in the western region on TCE is not significant. Regarding resource endowment heterogeneity, the industrial co-agglomeration in non-resource-based cities has a greater promoting effect on TCE than that in resource-based cities. [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]

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]

On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully. [ABSTRACT FROM AUTHOR]

Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions. [ABSTRACT FROM AUTHOR]

China's Green Space System Planning (GSSP) research has gradually expanded from central urban areas to municipal and provincial scales in recent years. Besides, the research on the role of green space in the water environment has also attracted much attention. However, the study of green corridors usually ignored hydrological data, which widespread absence especially in the large area scale. And the scale of green corridor construction mainly focused on central urban areas. This paper took China's Fujian province as an example. Based on the DEM elevation data, the article identified blue corridors without hydrological data. In addition, the green corridors were determined based on the land use data. According to the green corridors and blue corridors protection, we identified the ecological networks and nodes by the network analysis method. The results showed that the blue corridors identified by DEM data were consistent with the hydrological status quo. The regional status of the identified ecological networks and nodes were basically in line with their characteristics, proving the value of the planning methods. Finally, based on the identification results, suggestions for Fujian's ecological networks and nodes are put forward. [ABSTRACT FROM AUTHOR]

The construction models of smart cities and low-carbon cities are crucial for advancing global urbanization, enhancing urban governance, and addressing major urban challenges. Despite significant advancements in smart and low-carbon city research, a consensus on their coupling coordination remains elusive. This study employs mixed-method research, combining qualitative and quantitative analyses, to investigate the coupling coordination between urban smart performance (SCP) and low-carbon level (LCL) across 52 typical smart and low-carbon pilot cities in China. Independent evaluation models for SCP and LCL qualitatively assess the current state of smart and low-carbon city construction. Additionally, an Entropy–TOPSIS–Pearson correlation–Coupling coordination degree (ETPC) analysis model quantitatively examines their relationship. The results reveal that smart city initiatives in China significantly outperform low-carbon city development, with notable disparities in SCP and LCL between eastern, non-resource-based, and central cities versus western, resource-dependent, and peripheral cities. A strong positive correlation exists between urban SCP and overall LCL, with significant correlations in management, society, and economy, and moderate to weak correlations in environmental quality and culture. As SCP levels improve, the coupling coordination degree between the urban SCP and LCL systems also increases, driven primarily by economic, management, and societal factors. Conversely, the subsystems of low-carbon culture and environmental quality show poorer integration. Based on these findings, this study proposes an evaluation system for smart and low-carbon coupling coordination development, outlining pathways for future development from the perspective of urban complex systems. [ABSTRACT FROM AUTHOR]

Based on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a spatial perspective shows that green technological innovation plays a partial mediating role between DIF and carbon emissions, with the mediating effect accounting for approximately 59.47%. The heterogeneity analysis suggests that the impact of DIF on the reduction of carbon emissions is more pronounced in large and medium-sized cities and eastern regions. Further discussion reveals that the carbon reduction effect of DIF is also influenced by green technological innovation and industrial structure upgrading, showing threshold effects with marginal decreases and gradual increases, respectively. [ABSTRACT FROM AUTHOR]

Yellow River Basin (YRB) is a pivotal region for energy consumption and carbon emissions (CEs) in China, with cities emerging as the main sources of regional CEs. This highlights their critical role in achieving regional sustainable development and China's carbon neutrality. Consequently, there is a pressing need for a detailed exploration of the urban spillover effects and an in-depth analysis of the complex determinants influencing CEs within the YRB. Remote sensing data provide optimal conditions for conducting extensive studies across large geographical areas and extended time periods. This study integrates DMSP/OLS and NPP/VIIRS nighttime light datasets for a longitudinal analysis of urban CEs in the YRB. Using a harmonized dataset from DMSP/OLS and NPP/VIIRS nighttime light from 2007 to 2021, this study quantifies CEs of 58 prefecture-level cities in the YRB. By combining ESDA, STIRPAT model and spatial econometric model, this investigation further clarifies empirically the spatial spillover effects and driving factors of urban CEs. The analysis delineates a phase-wise augmentation in urban CEs, converging towards a distinct spatial distribution characterized by "lower reach > middle reach > upper reach". The spatial autocorrelation tests unravel a complex interplay between agglomeration and differentiation patterns within urban CEs, underscored by pronounced spatial lock-in phenomena. Significantly, this study demonstrates that urbanization, economic development, energy consumption structure, green coverage rate, industrial structure, population, technological progress, and FDI each exhibit varied direct and indirect effect on urban CEs. Furthermore, it elaborates on potential policy implications and future research directions, offering crucial insights for formulating CEs mitigation strategies to advance sustainable development. [ABSTRACT FROM AUTHOR]

Green finance (GF) has emerged as a promising tool to promote low-carbon development, while knowledge is rather limited regarding the underlying mechanism. This article aims to address this void by constructing a city-level GF index covering seven dimensions and identifying the main pathways through which GF can facilitate the low-carbon development of cities. Using a balanced panel data covering 277 Chinese cities from 2010 to 2020, the results show that: (1) China's GF development exhibits an overall spatial differentiation of 'high in the east and low in the west', while the distribution of carbon intensity (CI) displays an overall spatial differentiation of 'high in the north and low in the south'; (2) GF significantly decreases CI of cities, which is robust to employing DID strategies and IV estimations; (3) The role of GF on CI varies with the level of CI whereas not with the level of GF. Specifically, the mitigating effect of GF on CI is significant in both high GF and low GF groups, but only in high CI group; and (4) GF promotes low-carbon transition of cities through mainly on adjusting industrial structure rather than stimulating technological innovation. Despite we also demonstrate green finance enhances green innovation, due to multi-factors, such technology progress it brings may not always translate into a tangible improvement in green productivity. For most developing countries including China, the future policy objective of green finance should focus on enhancing sustainable technological progress. [ABSTRACT FROM AUTHOR]

New urbanization (NU) and ecological welfare performance (EWP) play pivotal roles in achieving sustainable urban development, with both emphasizing social equity and environmental management. Exploring the coordinated relationship between EWP and NU is invaluable for understanding the symbiotic interplay between humans and nature. We constructed a framework to elucidate the coupling mechanism of EWP and NU from the perspective of systems theory. We quantified the levels of NU and EWP utilizing the entropy weighting method and the super-efficient SBM method, respectively. Furthermore, we assessed the degree of coupling coordination between the two using the coupling coordination degree model (CCDM). Spatial and temporal evolution analysis was conducted, and factors influencing the degree of coupling coordination between EWP and NU were explored through a spatial–temporal geographically-weighted regression model (GTWR). The results indicate: (1) During the study period, the average annual increase in EWP in the study area was 2.59%, with a narrowing relative gap between cities. Conversely, the average annual increase in the level of NU was 7.6%, with demographic and economic dimensions carrying the highest weights. (2) The type of coupling coordination between EWP and NU transitions from basic coordination to moderate coordination, with the development of EWP lagging behind that of NU. (3) City size demonstrates a positive yet diminishing trend on the coupling coordination level, with economic development exerting the greatest influence and exhibiting a "V" trend, while the impact of green technology innovation diminishes negatively. Additionally, regional disparities are significant, with city size exhibiting a negative impact in areas of high population density and low economic levels, and green technology innovation showing notable polarization characteristics in core cities. These findings serve as a foundation for fostering coordinated ecological development amid the rapid urbanization process of the Chengdu–Chongqing Economic Circle. [ABSTRACT FROM AUTHOR]

Improving access to HIV/AIDS healthcare services is of great concern to government and policymakers striving to strengthen overall public health. How to reasonably allocate HIV/AIDS healthcare resources and maximize the equality of access to healthcare services across subdistrict areas has become an urgent problem to be solved. However, there is limited research on this topic in China. It is necessary to evaluate spatial accessibility to improve the accessibility and equity of HIV/AIDS healthcare services. In this study, the improved multi-modal two-step floating catchment area (2SFCA) and inverted 2SFCA (i2SFCA) methods are used to measure the spatial accessibility of HIV/AIDS healthcare services and the crowdedness of the healthcare sites in Shandong Province, China. Then, the theoretical supply and the optimal spatial distribution of resources are calculated and visualized by minimizing the accessibility gaps between demand locations. This study showed that the spatial accessibility of HIV/AIDS service resources in Shandong Province was concentrated and unevenly distributed, and the accessibility scores in the marginal areas of prefecture-level cities were significantly lower than those in other areas. Regions with a large number of doctors had significantly higher levels of spatial accessibility. The ART accessibility scores in the southwest of Shandong Province were higher than those in other regions. As the travel friction coefficient increased, the accessibility scores formed an approximately circular cluster distribution centered on the healthcare sites in geographical distribution. More ART drugs needed to be supplied in marginal areas and more doctors were needed to work on HIV/AIDS in urban areas to address the spatial distribution imbalance of HIV/AIDS healthcare services. This study profoundly analyzed the spatial accessibility of HIV/AIDS healthcare services and provided essential references for decision-makers. In addition, it gives a significant exploration for achieving the goal of equal access to HIV/AIDS healthcare services in the future. [ABSTRACT FROM AUTHOR]

The rising sentiment challenges of the metropolitan residents may be attributed to the extreme temperatures. However, nationwide real-time empirical studies that examine this claim are rare. In this research, we construct a daily extreme temperature index and sentiment metric using geotagged posts on one of China's largest social media sites, Weibo, to verify this hypothesis. We find that extreme temperatures causally decrease individuals' sentiment, and extremely low temperature may decrease more than extremely high temperature. Heterogeneity analyses reveal that individuals living in high levels of PM2.5, existing new COVID-19 diagnoses and low-disposable income cities on workdays are more vulnerable to the impact of extreme temperatures on sentiment. More importantly, the results also demonstrate that the adverse effects of extremely low temperatures on sentiment are more minor for people living in northern cities with breezes. Finally, we estimate that with a one-standard increase of extremely high (low) temperature, the sentiment decreases by approximately 0.161 (0.272) units. Employing social media to monitor public sentiment can assist policymakers in developing data-driven and evidence-based policies to alleviate the adverse impacts of extreme temperatures. [ABSTRACT FROM AUTHOR]

Based on dynamic monitoring data on China's population, by using complex networks, spatial analysis and mathematical measurement, this study reveals the spatial characteristics and influencing factors of the network of flows of highly educated talents in the Yangtze River Delta region from the national and local perspectives. In the two perspectives, the network has strong isomorphism and certain differences. The in-flow of highly educated talents from cities with high administrative levels and more developed economies to Shanghai constitutes the core of the entire network. From a national perspective, highly educated talents tend to converge to the Yangtze River Delta region. From a local perspective, it was found that these talents cluster towards a limited number of cities in the region. From both perspectives, the flow network has developed into a "core-periphery" progressive hierarchical structure, with Shanghai becoming the sole core city. There is little difference in the influencing factors of talent mobility from both macro and meso perspectives. Highly educated talents would frequently flow between cities with strong economic development levels, and cities with high education level, scientific and technological level, complete infrastructure, and good aesthetics. However, geographical distance still plays a hindering role in the flow of highly educated talents, and factors such as cultural identity, institutional, and social modality differences among regions also have a certain effect on the flow of these talents. [ABSTRACT FROM AUTHOR]

Based on panel data from 210 prefecture-level cities in China from 2003 to 2021, this study employs the Time-Varying Differences-in-Differences (Time-Varying DID) approach to systematically examine the impact of smart city construction on pollution emissions and its underlying mechanisms. Additionally, the Propensity Score Matching–Differences-in-Differences method is employed for further validation. The research findings indicate that Smart City Construction (SCC) significantly reduces urban Volume of Sewage Discharge (VSD), sulfur dioxide emissions (SO2), and Emissions of Fumes and Dust (EFD), thereby mitigating pollution emissions (PE) and enhancing environmental quality. Mechanism analysis reveals that SCC achieves these effects through scale effects, structural effects, and technological effects. City heterogeneity analysis shows that provincial capital cities exhibit a stronger suppression effect on pollution emissions compared to non-provincial capital cities. Moreover, cities with lower levels of education attainment demonstrate a stronger ability to curb pollution emissions, while larger cities exhibit a more pronounced impact on mitigating pollution emissions. The marginal contributions of this study mainly consist of three aspects: Firstly, it enriches the literature on environmental impact factors by assessing, for the first time, the influence of SCC on PE. Secondly, a comprehensive approach is employed, integrating VSD, EFD, SO2 data, and economic and pollution data at the city level. Time-Varying DID is used to evaluate the policy effects of SCC. Finally, the study analyzes the impact mechanisms of SCC policy on environmental emissions from various perspectives. [ABSTRACT FROM AUTHOR]

China, the world leader in automobile production and sales, confronts the challenge of transportation emissions, which account for roughly 10% of its total carbon emissions. This study, utilizing real-world vehicle data from three major Chinese cities, assesses the impact of Battery Electric Vehicles (BEVs) on air quality. Our analysis reveals that BEVs, when replacing gasoline vehicles in their operational phase, significantly reduce emissions, with reductions ranging from 8.72 to 85.71 kg of CO2 per vehicle monthly. The average monthly reduction rate is 9.47%, though this effect is less pronounced during winter. Advanced BEVs, characterized by higher efficiency and newer technology, exhibit greater emission reduction benefits. While private BEVs generally contribute positively to environmental outcomes, taxi BEVs, due to their intensive usage patterns, show less environmental advantage and may sometimes worsen air quality. Looking ahead, we project substantial emission reductions from the replacement of gasoline vehicles with electric alternatives over the next decade. Policymakers are urged to adopt proactive measures, focusing on promoting medium to large electric vehicles and fostering the use of private and ride-hailing electric vehicles. [ABSTRACT FROM AUTHOR]

Digital economy is the indispensable pathway for driving industrial structural upgrading and fostering innovation and entrepreneurship in cities, ultimately facilitating China's economic transformation. Simultaneously, the enhancement of urban total factor productivity (TFP) serves as a crucial means to achieve high-quality economic development in cities. This study examines the specific impact of the digital economy on urban TFP using a panel data model with a sample of 285 Chinese prefecture-level cities from 2011 to 2019. Additionally, it employs a mediation effect model to test the mechanisms through which the digital economy influences urban TFP and utilizes a spatial Durbin model to analyze the spatial spillover effects of the digital economy on urban TFP. The research findings reveal the following key points: (1)The digital economy has an overall significantly positive impact on urban TFP. (2)The digital economy indirectly promotes urban TFP by encouraging the advancement of industrial structure and fostering innovation and entrepreneurship in cities. (3)The influence of the digital economy on urban TFP exhibits spatial spillover effects, where the digital economy in neighboring cities significantly enhances the TFP growth of local cities.The results of this study contribute to elucidating the mechanistic pathways through which the digital economy affects urban TFP, holding significant practical implications for achieving high-quality economic development in urban areas. [ABSTRACT FROM AUTHOR]

SO2 emissions have brought serious hidden danger to human health and environmental quality, thus hindering sustainable economic development. The development of high-speed rail indirectly has an important impact on SO2 emissions through its economic effects. Controlling SO2 emissions from the source has increasingly become the focus of many scholars, and it is very important to assess the environmental effects of high-speed rail on SO2 emissions reduction. We use the panel data of 285 cities in China from 2007 to 2017, and adopt the spatial Difference-in-Differences model to study the impact of the opening of high-speed rail on SO2 emissions. We also introduce an improved spatial DID model that distinguishes neighboring treatment groups and neighboring control groups to test the spatial spillover effect of high-speed rail on neighboring heterogeneous samples. We find that the opening of high-speed rail significantly reduces the city's SO2 emissions through the internal accumulation effect of technological innovation and industrial structure optimization and the urban external interaction mechanism of the cross-regional flow of production factors. Moreover, the spatial spillover effect of the opening of high-speed rail on neighboring cities is significantly positive, especially the spatial spillover effect of HSR on SO2 emissions from neighboring cities without HSR. In addition, heterogeneity analysis shows that the effect varies with the different cities' tiers and income levels. These findings are conducive to accurately assessing the environmental effects of high-speed rail, and provide important policy references for achieving sustainable development and reducing SO2 emissions. [ABSTRACT FROM AUTHOR]

Urban agglomerations have become a new trend in the development of urbanization and regionalization in the world today. The construction of urban agglomerations has brought rapid economic development as well as a series of ecological and environmental problems, especially the impact on urban air quality. How to understand and evaluate the impact of urban agglomeration construction on air quality is a key issue that requires attention. City cluster construction is equivalent to a "quasi-natural experiment". This study empirically examines the impact of urban agglomeration construction on air quality in southwest China by constructing a PSM–DID model. It is found that: (1) City cluster construction has significantly improved urban air quality in urban clusters with lagging and forward-looking effects on air quality. (2) In terms of influencing factors, the level of economic development considerably improves the air quality of urban cluster cities, the industrial structure severely deteriorates the air quality of these cities, and meteorological factors highly affect their air quality. Among them, average annual urban rainfall significantly reduces urban air pollutant concentrations in urban clusters, average annual temperature significantly increases urban air pollutant concentrations, and average annual wind speed can reduce urban air pollutant concentrations. (3) Urban agglomerations are spatially heterogeneous in their impact on air quality. In this context, the topographical conditions and the level of development of urban agglomerations have a non-negligible influence on pollutant concentrations. (4) The distribution pattern of air quality pollutant concentrations in each urban agglomeration is unstable, and there are large differences in these concentrations between different urban agglomerations. [ABSTRACT FROM AUTHOR]

The sustainable development of urban agglomerations plays a pivotal role in national and global efforts to reduce emissions. By focusing on the efficient exchange and optimization of energy consumption across various sectors, the sustainable development of energy systems within urban agglomerations can be achieved. However, the overall impact of the cross-sector energy optimization and complementarity has not been quantitatively analyzed. Here, we focused on the Yangtze River Delta (YRD) urban agglomeration in China and proposed an optimization framework for energy, environment, and economy. The framework considered four sectors: transportation sector, power sector, industry sector, and building sector, in order to determine the most sustainable development pathway for the urban agglomeration. The optimization model considers total costs and greenhouse gas emissions reduction as the objectives and utilizes technologies as constraints to optimize the pathway. We found that this optimization strategy resulted in a 53.1 billion tons increase in CO2 emissions reduction in the region. The results of emission reduction varied across sectors, ranging from 4.5 to 22.2 billion tons CO2 equivalent, and across cities, ranging from 7.1 to 4688.1 Mt. The results suggest that the core cities in the urban agglomeration can take on a leadership role. By promoting cross-sector collaboration and implementing energy recycling, the energy efficiency of surrounding cities can be greatly improved, leading to the sustainable development of the urban agglomeration. [ABSTRACT FROM AUTHOR]

The characteristics of common prosperity include harmonious relationships between humans and the environment, as well as sustainable economic and social growth. The process of achieving common prosperity will necessarily have an impact on carbon emissions. In this article, panel statistics collected from 30 Chinese provinces and cities between the years 2006 and 2020 are utilized to assess the level of common prosperity and the intensity of carbon emissions in China. Then the SDM model is applied to explore the effects of the common prosperity level on the intensity of carbon emissions. The findings reveal that: (i) The common prosperity level in China has shown an increasing tendency. Between 2006 and 2020, the mean level of common prosperity increased from 0.254 to 0.486. From the regional perspective, eastern China has seen greater levels of common prosperity than central China, while central China has experienced greater levels of common prosperity than western China; regional disparities in the degree of common prosperity are substantial among Chinese provinces from 2006 to 2020; the common prosperity level is relatively high in economically developed provinces and relatively low in economically backward provinces. (ii) China's carbon emission intensity shows a continuous downward tendency. The annual average intensity of China's carbon emissions decreased from 4.458 in 2006 to 2.234 in 2020. From the regional perspective, the three main regions' carbon emission intensity likewise exhibits a decline in tendency between 2006 and 2020; still, western China continues to have the greatest carbon emission intensity, following central China, while eastern China has the smallest; however, certain provinces, notably Inner Mongolia and Shanxi, continue to have high carbon emission intensity. (iii) China's common prosperity level and carbon emission intensity both exhibit positive spatial autocorrelation at a 1% significant level under the adjacency matrix. The spatial agglomeration effect is significant, and adjacent provinces can affect each other. (iv) The SDM (Spatial Durbin Model) model test with fixed effects finds that the increase in the level of common prosperity suppresses the intensity of carbon emissions in the local area and neighboring regions. (v) The mediating effects model indicates that the process of common prosperity suppresses carbon emission intensity through high-quality economic development, narrowing the income disparity, and the development of a sharing economy. [ABSTRACT FROM AUTHOR]

In the context of "space of flows", city-based innovation correlation in driving economic growth is no longer limited to the traditional hierarchical structure. It is of great significance to explore Chinese cities innovation association network from the perspective of high-tech zones which gather a large number of innovation resources. Here our report is to provide new ideas for improving the innovation capability of high-tech zones and accelerating the construction of Chinese high-quality innovation system. Here we take 142 cities with high-tech zones as research samples, and explore the characteristics and influencing factors of spatial network of city-based innovation correlation in China, through modified gravity modelsocial, network analysis and QAP analysis. The results show that city-based innovation network is not closely connected, the number of redundant connection channels is low efficiency, showing a four-level spatial pattern of "Z" shaped spindle. Among them, degree centrality of cities in eastern China is higher than that in the western region, the core cities in central China play a bridging role, and western remote cities are easily affected by related cities. Moreover, there are four innovation cohesion subgroups, including the northern hinterland subgroup, the eastern coastal subgroup, the southern subgroup and the western cooperation subgroup. Furthermore, the results of the influencing factors analysis show the differences in administrative level, economic development level, openness to the outside world, and investment in technology are conducive to the innovation association between cities, while the similarities in spatial adjacency and industrial structure will promote the strong innovation association between cities. [ABSTRACT FROM AUTHOR]

Enhancing the effectiveness of urban green innovation is a powerful strategy for advancing urban sustainability. A strong urban innovation ecosystem is a crucial building block for advancing urban green innovation's effectiveness. We use the fsQCA method to investigate the pathways and models of innovation ecosystems to promote the green innovation efficiency of cities from a histological perspective, using 71 innovative cities in China as cases. This method is based on the DEA-SBM model to measure the green innovation efficiency of cities and the Necessary Conditions Analysis. According to our analysis, individual innovation factors are not required to increase urban green innovation efficiency. But cities with good openness can attract creative forces and foster open innovation, which is essential for producing high levels of green innovation efficiency in cities. The innovation subject-balanced development model, the innovation environment-innovation asset dual drive model, and the innovation subject-open drive model have all been identified as additional models to support urban innovation efficiency. Finally, we discovered that it is not possible to increase the efficiency of green innovation in the city when each innovation factor in the city is performing poorly, and when there is also a lack of innovation subject and system openness. This study attempts to offer fresh theoretical angles and a variety of urban low-carbon development pathways. [ABSTRACT FROM AUTHOR]

As China's economy transitions, environmental issues have become a major concern. This study examines the impact of Ambient Air Quality Standards (AAQS) on urban air quality using panel data from 284 cities in China from 2006 to 2019. The study utilizes DID (Difference-in-Difference) models to analyze the regulatory effects of AAQS and its spatial spillover. Additionally, the serial multiple mediation models are constructed to investigate the role of green innovation. The findings reveal that the AAQS positively affects urban air quality, albeit with a notable "hysteresis effect." Local implementation of AAQS worsens air quality in neighboring cities within a distance of 400 km, but beyond 400 km, the effect is reversed. Heterogeneity analysis shows that AAQS improves air quality in central cities, large-sized and medium-sized cities, cities with weak environmental governance, and resource-based cities. Mechanism tests suggest that AAQS may enhance urban air quality by promoting green innovation and optimizing industrial structure. Especially, either the energy-use effect or industrial-structure effect triggered by green innovation can contribute to the improvement of urban air quality. [ABSTRACT FROM AUTHOR]

Urban green technology innovation (UGTI) is strongly tied to environmental regulations, which can successfully balance economic and environmental benefits. Selecting the panel data for 280 Chinese cities during 2006–2019, we take the energy saving and emission reduction (ESER) demonstration city policy as a quasi-natural experiment, then employ the difference-in-differences model to examine the effect and its mechanisms of ESER policy on UGTI. Empirical results show that the ESER policy can significantly promote UGTI, especially in the western region, the northern region, and cities with weak government environmental attention. At the same time, China's ESER policy has a stronger promoting effect on UGTI in cities where environmental targets are more stringent. Mechanism analysis shows that the policy mainly promotes UGTI through two channels: increasing the proportion of science and technology expenditure in fiscal expenditure and upgrading the structure of the industry. In addition, we find that the development of UGTI has positive environmental effects by lowering carbon emissions and air pollution. The findings not only enrich the literature on environmental regulation policies and UGTI at the theoretical level, but also provide references for policymakers to specific implementation methods in further enforcing environmental regulation policies to improve UGTI. [ABSTRACT FROM AUTHOR]

Rural mobility inequality is an important aspect of inequality-focused Sustainable Development Goals. To reduce inequality and promote global sustainable development, more insight is needed into human mobility patterns in rural areas. However, studies on rural human mobility are scarce, limiting our understanding of the spatial and social gaps in rural human mobility and our ability to design policies for social equality and global sustainable development. This study, therefore, explores human mobility patterns in rural China using mobile phone data. Mapping the relative frequency of short-distance trips across rural towns, we observed that geographically peripheral populations tend to have a low percentage of short-distance flows. We further revealed social gaps in mobility by fitting statistical models: as travel distances increased, human movements declined more rapidly among vulnerable groups, including children, older people, women, and low-income people. In addition, we found that people living with low street density, or in rural towns in peripheral cities with long distances to city borders, are more likely to have low intercity movement. Our results show that children, older adults, women, low-income individuals, and geographically peripheral populations in rural areas are mobility-disadvantaged, providing insights for policymakers and rural planners for achieving social equality by targeting the right groups. [ABSTRACT FROM AUTHOR]

Through spatial–temporal scanning statistics, the spatial–temporal dynamic distribution of pulmonary tuberculosis incidence in 31 provinces and autonomous regions of China from 2008 to 2018 is obtained, and the related factors of spatial–temporal aggregation of tuberculosis in China are analyzed to provide strong scientific basis and data support for the prevention and control of pulmonary tuberculosis. This is a retrospective study, using spatial epidemiological methods to reveal the spatial–temporal clustering distribution characteristics of China's tuberculosis epidemic from 2008 to 2018, in which cases data comes from the China Center for Disease Control and prevention. Office Excel is used for general statistical description, and the single factor correlation analysis adopts χ2 Test (or trend χ2 Inspection). Retrospective discrete Poisson distribution space time scanning statistics of SaTScan 9.6 software are used to analyze the space time dynamic distribution of tuberculosis incidence in 31 provinces, cities and autonomous regions in China from 2008 to 2018. ArcGIS 10.2 software is used to visualize the results. The global spatial autocorrelation analysis adopts Moran's I of ArcGIS Map(Monte Carlo randomization simulation times of 999) is used to analyze high-risk areas, low-risk areas and high-low risk areas. From 2008 to 2018, 10,295,212 cases of pulmonary tuberculosis were reported in China, with an average annual incidence rate of 69.29/100,000 (95% CI: (69.29 ± 9.16)/100,000). The annual GDP (gross domestic product) of each province and city showed an upward trend year by year, and the number of annual medical institutions in each province and city showed a sharp increase in 2009, and then tended to be stable; From 2008 to 2018, the national spatiotemporal scanning statistics scanned a total of 6 clusters, including 23 provinces and cities. The national high-low spatiotemporal scanning statistics of the number of pulmonary tuberculosis cases scanned a total of 2 high-risk and low-risk clusters. The high-risk cluster included 8 provinces and cities, and the low-risk cluster included 12 provinces and cities. The global autocorrelation Moran's I index of the incidence rate of pulmonary tuberculosis in all provinces and cities was greater than the expected value (E (I) = −0.0333); The correlation analysis between the average annual GDP and the number of pulmonary tuberculosis cases in each province and city from 2008 to 2018 was statistically significant. From 2008 to 2018, the spatial and temporal scanning and statistical scanning areas of tuberculosis incidence in China were mainly concentrated in the northwest and southern regions of China. There is an obvious positive spatial correlation between the annual GDP distribution of each province and city, and the aggregation degree of the development level of each province and city is increasing year by year. There is a correlation between the average annual GDP of each province and the number of tuberculosis cases in the cluster area. There is no correlation between the number of medical institutions set up in each province and city and the number of pulmonary tuberculosis cases. [ABSTRACT FROM AUTHOR]

Effective measures to improve road accessibility during storms are required as traffic congestion caused by storm floods increasingly constrains the efficiency of urban commuting. However, flood impacts on urban road connectivity are not yet well assessed due to inaccurate simulation of flood processes in urban areas where high-resolution data for drainage networks and gauged hydrological data are insufficient. Thus, this study assesses flood impacts on road network connectivity in an urban area of southern China through joint modeling of 1-D hydrodynamic processes in drainage networks and 2-D flood inundation processes on roads using MIKE Urban and MIKE 21. High-resolution DEM images of 5 m and a drainage network of 5635 pipelines were used for urban hydrological simulation. Flood depths were gauged for model calibration and validation by recruited volunteers in the context of citizen science. The results show that road network connectivity decreases as rainfall increases. More than 40% of road connectivity is lost in the study area when a 1-in-100-year return period rainfall occurs. The study results can help to inform more adaptive strategies for local flood control. The study methods are also applicable to improving urban hydrological modeling in broader regions. [ABSTRACT FROM AUTHOR]

Acute haemorrhagic conjunctivitis (AHC) outbreaks are reported frequently in China. However, the transmissibility of AHC remains unclear. This study aimed to calculate the transmissibility of the disease with and without interventions. An AHC outbreak dataset from January 2007 to December 2016 in different schools was built in Hunan Province. A Susceptible-Infectious-Recovered (SIR) model was adopted to calculate the effective reproduction number (Reff) of AHC. Reff was divided into two parts (Runc and Rcon) where Runc and Rcon represent the uncontrolled and controlled Reff , respectively. Based on Runc and Rcon, an index of effectiveness of countermeasures (Ieff) was developed to assess the effectiveness of countermeasures in each outbreak. During the study period, 34 AHC outbreaks were reported in 20 counties of 9 cities in Hunan Province, with a mean total attack rate of 7.04% (95% CI: 4.97–9.11%). The mean Runc of AHC outbreaks was 8.28 (95% CI: 6.46–10.11). No significance of Runc was observed between rural and urban areas (t = −1.296, P = 0.205), among college, secondary, and primary schools (F = 0.890, P = 0.459), different levels of school population (F = 0.738, P = 0.538), and different number of index cases (F = 1.749, P = 0.180). The most commonly implemented countermeasures were case isolation, treatment, and health education, followed by environment disinfection, symptom surveillance, and school closure. Social distance, prophylaxis, and stopping eye exercises temporary were implemented occasionally. The mean value of Rcon was 0.16 (range: 0.00–1.50). The mean value of Ieff was 97.16% (range: 71.44–100.00%). The transmissibility of AHC is high in small-scale outbreaks in China. Case isolation, treatment, and health education are the common countermeasures for controlling the disease. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) is one major anthropogenic modification to the Earth system that transcends its physical boundary. Using MODIS data from 2003 to 2012, we showed that the UHI effect decayed exponentially toward rural areas for majority of the 32 Chinese cities. We found an obvious urban/rural temperature 'cliff', and estimated that the footprint of UHI effect (FP, including urban area) was 2.3 and 3.9 times of urban size for the day and night, respectively, with large spatiotemporal heterogeneities. We further revealed that ignoring the FP may underestimate the UHI intensity in most cases and even alter the direction of UHI estimates for few cities. Our results provide new insights to the characteristics of UHI effect and emphasize the necessity of considering city- and time-specific FP when assessing the urbanization effects on local climate. [ABSTRACT FROM AUTHOR]