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Atmospheric pollutants PM2.5 and CO2 share similar sources and impact mechanisms. Green innovations and urban greening significantly reduce these pollutants while promoting economic growth. However, the synergies and trade-offs between carbon reduction, pollution control, green expansion, and economic growth remain understudied. This paper examines 110 cities in the Yangtze River Economic Belt (YREB), China's premier green development site, as a unified system. Using fractional-order synthesis analysis, this paper constructs an assessment indicator system and measures synergy with a coupled coordination degree model. The driving factors are explored using a system-generalized method of moments estimation. The findings indicate that most cities in the YREB are at an intermediate coordination stage. The coupling of greening with carbon reduction, pollution control, and growth has a low degree, highlighting an urgent need to strengthen greening efforts. Key drivers include the digital economy, advanced industrial structure, innovative talent aggregation, infrastructure construction, financial investment, and marketization. The digital economy significantly influences all regions of the Yangtze River. Notable heterogeneity exists in the impact of other drivers across different regions. These results offer valuable policy insights for managing carbon emissions and pollutants, contributing to sustainable urban development.

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It is of great significance to explore the regional differences of land use carbon emission （LUCE） in the Yangtze River Economic Belt and the path of coordinated emission reduction for regional sustainable development. Based on the LUCE estimation method, this study scientifically calculated the LUCE of the three major urban agglomerations of the Yangtze River Economic Belt （Yangtze River Delta, middle reaches of the Yangtze River, and Chengdu-Chongqing urban agglomeration） from 2010 to 2020. Kernel density estimation and the spatial convergence model were used to study the dynamic evolution, regional differences, and convergence characteristics of LUCE. The results showed that： ① The carbon absorption of forest land, water areas, grassland, and unused land were relatively small in terms of carbon emissions from cultivated land and construction land. The carbon emission of construction land increased gradually, whereas the carbon absorption of four carbon sinks fluctuated little during the study period. ② The core density curves of different urban agglomerations showed different distribution patterns, extensibility, and polarization characteristics but generally tended to be balanced. ③ From 2010 to 2020, the LUCE of the Yangtze River Economic Belt as a whole showed the spatio-temporal characteristics of increasing first and then decreasing and high in the east and low in the west. The LUCE of the central cities of the three urban agglomerations were at the highest level steadily, and stable coupling mechanisms had not been established between the economic development level and the ecological environment. ④ The LUCE of the three urban agglomerations in the Yangtze River Economic Belt all had absolute ß convergence and also had conditional ß convergence under the model control variables such as economic development level, urbanization level, industrial structure, population density, and environmental regulation, etc., and the conditional convergence speed was greater than the absolute convergence speed in each region. The convergence speed of the Yangtze River Delta urban agglomeration was the slowest. The above conclusions provide support for the coordinated emission reduction path of the three urban agglomerations in the Yangtze River Economic Belt and are also conducive to actively and steadily promoting the realization of the goals of carbon peak and carbon neutralization.

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Ecosystem services (ESs) and their changes are complex processes driven by multiple factors. Understanding the trade-off and synergy between ESs and their driving factors is essential for achieving effective management of ESs and human well-being. Taking the Yangtze River Economic Belt as the research area, this study analyzed the temporal and spatial variation characteristics of four ESs including water yield, soil conservation, carbon sequestration, and food supply from 2000 to 2020. Correlation analysis and geographically weighted regression were used to identify and quantify the trade-off and synergy between ESs. On this basis, the partial least squares structural equation model was used to explore the impact of natural and human activities on ESs, and then the driving mechanism of ESs relationship change was analyzed via GeoDetector. The results showed that:① During the 20 years, the average annual carbon sequestration increased from 946.14 t·km-2 to 1 202.73 t·km-2, and the average food supply increased from 32.73×104 Yuan·km-2 to 127.22×104 Yuan·km-2. Water yield and soil conservation increased to a lesser degree. ② On the whole, carbon sequestration and soil conservation and food supply and water yield showed synergy, and other ESs were trade-offs. The relationship between ESs varied in different regions. ③ Terrain and climate were important driving factors for ESs and the trade-off and synergy of multiple ESs. Among them, structural equation model results showed that climate had a positive impact on water yield (S=0.73), and terrain had a negative impact on food supply (S=-0.57). GeoDetector results revealed that the main driving factors affecting the spatial relationship between carbon sequestration and water yield were elevation (q=0.38) and precipitation (q=0.19). The results of this study can provide a scientific reference for the sustainable management of ESs in the Yangtze River Economic Belt and the realization of the coordinated development of ecological environment protection and social economy in the region.

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Clarifying the mechanism of influence of urban form on carbon emissions is an important prerequisite for achieving urban carbon emission reduction. Taking the Yangtze River Economic Belt as an example, this study elaborated on the general mechanism of urban form on carbon emissions, used multi-source data to quantitatively evaluate the urban form, and explored the impacts of urban form indicators on carbon emissions from 2005 to 2020 at global and sub-regional scales with the help of spatial econometric models and geodetector, respectively. The results showed that:① The carbon emissions of the Yangtze River Economic Belt increased from 2 365.31 Mt to 4 230.67 Mt, but the growth rate gradually decreased. Its spatial distribution pattern was bipolar, with high-value areas mainly distributed in core cities such as Shanghai and Chongqing and low-value areas concentrated in the western regions of Sichuan and Yunnan. ② The area of construction land in the study area expanded over the past 15 years, but the population density of construction land had been decreasing. The degree of urban fragmentation was decreasing, and the difference between cities was also progressively narrowing. The average regularity of urban shape improved, and the compactness increased significantly. ③ All indicators of urban scale had significant positive effects on carbon emissions at the global scale, urban fragmentation had a significant negative effect in 2005, and the effective mesh size (MESH) indicator of urban compactness showed a significant negative correlation with carbon emissions in the study period. ④ Total class area, patch density, and effective mesh size had the most significant impacts on carbon emissions in upstream cities. Effective mesh size, mean perimeter-area ratio, and total class area had higher influences in midstream cities. Effective mesh size, percentage of like adjacencies, and largest patch index were the key factors to promote carbon reduction in downstream cities. Cities in different regions should comprehensively consider the impacts of various urban form indicators on carbon emissions and then optimize their urban form to promote sustainable development.

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Excess nitrogen and phosphorus inputs are the main causes of aquatic environmental deterioration. Accurately quantifying and dynamically assessing the regional nitrogen and phosphorus pollution emission (NPPE) loads and influencing factors is crucial for local authorities to implement and formulate refined pollution reduction management strategies. In this study, we constructed a methodological framework for evaluating the spatio-temporal evolution mechanism and dynamic simulation of NPPE. We investigated the spatio-temporal evolution mechanism and influencing factors of NPPE in the Yangtze River Economic Belt (YREB) of China through the pollution load accounting model, spatial correlation analysis model, geographical detector model, back propagation neural network model, and trend analysis model. The results show that the NPPE inputs in the YREB exhibit a general trend of first rising and then falling, with uneven development among various cities in each province. Nonpoint sources are the largest source of land-based NPPE. Overall, positive spatial clustering of NPPE is observed in the cities of the YREB, and there is a certain enhancement in clustering. The GDP of the primary industry and cultivated area are important human activity factors affecting the spatial distribution of NPPE, with economic factors exerting the greatest influence on the NPPE. In the future, the change in NPPE in the YREB at the provincial level is slight, while the nitrogen pollution emissions at the municipal level will develop towards a polarization trend. Most cities in the middle and lower reaches of the YREB in 2035 will exhibit medium to high emissions. This study provides a scientific basis for the control of regional NPPE, and it is necessary to strengthen cooperation and coordination among cities in the future, jointly improve the nitrogen and phosphorus pollution tracing and control management system, and achieve regional sustainable development.

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Urban ecological spaces are effective thermoregulators under global warming. However, the cooling efficiency of urban ecological spaces during the urbanization has not been studied comprehensively. Here, we investigate the spatio-temporal dynamics of Urban Cold Island (UCI) intensity in 11 typical cities of the Yangtze River Economic Belt (YREB). We determined the impact of ecological landscape trends on these dynamics by using GlobalLand and MODIS 8 d mean land surface temperature (LST) data for three periods (2000, 2010, and 2020), and the landscape pattern index and diversity index. We found that in the past 20 years, the built-up area has increased by sixfold; 62.53 % and 37.47 % of YREB were warming or cooling, with 71.22 % of the daytime cooling and 93 % of the nighttime warming. The average UCI intensity of YREB has increased from 0.518 to 0.847 and is negatively correlated with LST with a decreasing slope. As the UCI intensity of green spaces increased, that of blue spaces decreased. Surface area and landscape pattern are the key determinants of UCI intensity in blue and green spaces, respectively, especially the landscape shape index (LSI). Therefore, maintaining ecological spaces, enriching the structural integrity of green spaces, and improving blue space connectivity can help cities at different development levels cope with heat stress during regional urbanization.

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The digital economy (DIE), a new economic form with digitalization at its core, has become an important driving force for promoting regional economy development. In the context of the COVID-19 pandemic, exploring the impact path of the DIE on carbon emission efficiency (CEE) is conducive to giving full play to the "carbon-reduction-and-efficiency-enhancement" role of the DIE, and to promoting the realization the "dual carbon" goal of carbon peak and carbon neutrality. In this paper, the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB) are taken as study areas, the panel Tobit model is used to explore the impact of the DIE on CEE, and the intermediary-effect model and threshold-effect model are constructed to test the intermediary and threshold effects of technological innovation, respectively. The results show that the DIE has a U-shaped nonlinear impact on CEE in both the YRB and the YREB and that the impact has regional heterogeneity. Technological innovation can play a mediating effect between the DIE and CEE, whereas the mediating effect in the YRB is stronger than that in the YREB. Technological innovation has a threshold effect on the DIE to improve CEE, while the threshold value in the YREB is higher than that in the YRB. Furthermore, this paper proposes some suggestions to guide regional low-carbon and sustainable development.

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Inclusive green growth has garnered significant attention from governments and international organizations worldwide. Utilizing data from 282 cities in China spanning from 2010 to 2020, this study employs the dual machine learning model and the chain mediated effect model to delve into the effects and internal mechanisms of the regional integration of Yangtze River Economic Belt on inclusive green growth. Our findings indicate that the regional integration of Yangtze River Economic Belt has a substantial influence on inclusive green growth, particularly in cities with a higher degree of marketization, non-industrial cities, and cities lacking natural resource advantages. Mechanistic analysis reveals that the regional integration of Yangtze River Economic Belt exerts its influence on inclusive green growth through three parallel development paths including enhancing urban innovation levels, fostering mass entrepreneurship, and promoting the advancement of digital financial inclusion. Furthermore, the chain mediated effect is supported. Additionally, the spatial spillover effect of target policy is observed. These findings offer empirical evidence regarding the impact of the regional integration of Yangtze River Economic Belt on inclusive green growth, and provide valuable insights for optimizing and enhancing inclusive green growth strategies in China and other emerging economies.

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The issue of global climate change has garnered increasing attention, with carbon emissions emerging as a significant challenge confronting the world today. As an important means of environmental management, river basin ecological compensation must break through the traditional thinking of "water-centric" and move towards the coordinated development of "pollution reduction". Therefore, the study chooses the watershed scale ecological compensation experiment carried out in the Yangtze River Economic Belt as a natural experiment. Based on the prefecture-level city panel data from 2008 to 2021, a double difference model is constructed to examine the impact of the basin horizontal ecological compensation policy on carbon emissions and its mechanism. The study shows that the inter-regional horizontal ecological compensation measures have an obvious inhibitory effect on carbon emissions in the region, and through a series of tests, the conclusion is stable. Mechanism testing shows that policy implementation achieves carbon emission reductions through two channels: improving financial development and promoting scientific and technological innovation. The results of heterogeneity analysis verify that the effect of policy implementation is affected by the dual factors of social economy and innovation and entrepreneurship and that key cities and cities with a high innovation and entrepreneurship environment produce higher carbon emission reduction benefits. The research conclusions provide policy suggestions for promoting watershed ecological compensation policies to achieve carbon emission reduction from three aspects: encouraging small and medium-sized watersheds to implement city-specific policies, promoting innovative technologies and establishing monitoring and evaluation mechanisms, and strengthening policy support and financial investment.

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Positioned in the era of the transformation of China's primary social contradictions, this study delves into the new connotations of regional coordinated development(RCD) from the perspective of "factors" coordination within the region and constructs an RCD evaluation system from five subsystems of regional economic coordination(REC), urban-rural coordination(URC), economic and social coordination(EASC), resource and environmental coordination(RAEC), and material and spiritual civilization coordination(MASCC). Then, the Entropy weight-TOPSIS model is used to evaluate the RCD levels of the 19 provinces located in the Yangtze River Economic Belt(YREB) and Yellow River Basin(YRB) from 2010 to 2019, and the two-way fixed-effects model is employed to illustrate the driving mechanisms of various influencing factors on the RCD in YRB and YREB. The results show that:(1)the RCD levels of YRB and YREB show a fluctuating upward trend during 2010 and 2019, however, both regions have low RCD levels, as seen by the mean RCD indices for YREB and YRB, which are only 0.433 and 0.309, respectively. (2) The RCD level of YREB is higher than that of YEB. In 2019, the "coordinated" provinces in YRB and YREB account for 37.50% and 81.82% of the total number of provinces in the basins, respectively, the "uncoordinated" and "low coordinated" provinces all located in YRB. (3) The RCD of YRB and YREB is significantly improved by REC, URC and RAEC, but not significantly positively by MASCC or EASC, and insufficient development of MASCC is the main contradiction limiting the increase in the RCD level of YRB, while the low level of EASC has become the main obstacle limiting the RCD of YREB. (4)Finally, based on the varying impact degrees and directions of different influencing factors on the RCD in YRB and YREB, the recommendations to promote RCD are proposed.

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Environmental regulation promotes industrial structure change and regional economic transformation through land use adjustment, which gets a new way to explore the path of reforming traditional industrialization and urbanization. Based on the panel data of 128 prefecture-level cities in China 's Yangtze River Economic Belt from 2000 to 2020, this paper uses the spatial Dubin model to analyze the impact of environmental regulation and land use efficiency on the upgrading of industrial structure, and sets the panel threshold model to examine the impact of environmental regulation on the upgrading of industrial structure by affecting land use efficiency. The results show that formal environmental regulation has a significant positive spatial effect on the rationalization and upgrading of industrial structure, which are 0.1734 and 0.2854 respectively. Informal environmental regulation has a negative spillover effect on neighboring provinces but not significant. Heterogeneous environmental regulation has obvious "double threshold effect" on industrial upgrading by affecting land use efficiency. When the threshold of environmental regulation intensity is 0.0315-0.0886, environmental regulation still inhibits land use efficiency and industrial structure upgrading. When the threshold value is greater than 0.0886, environmental regulation has a positive impact on land use efficiency but not significant. With the intensity of environmental regulation from weak to strong, it will produce a double threshold effect of "strong inhibition-weak inhibition-interaction promotion" on the upgrading of manufacturing structure through the adjustment of land use efficiency.

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Improving green water use efficiency is based on the synergy of reducing pollutants and carbon emissions, and effectively identifying its spatial development structure is a prerequisite for realizing the green transformation of water management. This paper adopted the slacks-based measure- "energy-environment-economy" (SBM-3E) model with carbon emission and pollution indicators as unanticipated outputs to measure the green water use efficiency of the 11 provinces (cities) in the Yangtze River Economic Belt from 2000 to 2018, then analyzed the efficiency network structure evolution by using the social network analysis method, and finally examined the drivers of efficiency networks. The results show that (1) the value of green water utilization efficiency decreases from 0.78 to 0.51, and its spatial distribution is downstream > middlestream > upstream, with the values of 0.41, 0.61, and 0.86, respectively. (2) The overall spatial network efficiency is gradually interconnected, with the density increasing from 0.32 to 0.6; it has undergone a structural evolution from "flat" to "inverted tower." The core-edge structure of the main body status within the basin has been strengthened. (3) The efficiency network is significantly influenced by water resource endowment, industrial structure, and foreign investment level. The conclusions are expected to provide useful insights for designing the basin's water protection policy and greening the region's development.

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From the emergence of the new coronavirus pandemic to extreme climatic catastrophes, the development and enhancement of urban ecological resilience has evolved into a critical and strategic imperative. Investigating the capacity of digital finance to promote urban ecological resilience bears substantial relevance to the sustainable advancement of urban centers. This study examines the influence of digital finance on urban ecological resilience by applying a benchmark regression model on data from 107 prefecture-level cities within the Yangtze River Economic Belt across 2011-2020. Additionally, this study delves into its mechanism and spatial spillover impacts via a mediating effect model and a spatial effect model. The findings revealed that (1) digital finance strengthens the ecological resilience of the locale and beneficially impacts the surrounding regions; (2) digital finance enhances urban ecological resilience by fostering technological innovation and reducing energy intensity; and (3) in the lower reaches of the Yangtze River, digital finance plays a greater role in improving urban ecological resilience. Cities with high level of traditional financial development, high level of economic development and high intensity of environmental regulation have a more obvious role in promoting urban ecological resilience. Within the paradigm of ecological civilization, it is advisable for governmental bodies to fortify inter-regional digital financial collaboration, refine the green financial infrastructure, and advocate for sustainable, low-carbon, high-quality urban development.

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Exploring the effect of local government multi-objective competition on the transfer of polluting industries is of great practical significance for promoting the high-quality development in the Yangtze River Economic Belt. This paper adopted the extended shift-share analysis method to measure the scale of inter-provincial transfer of polluting industries in the Yangtze River Economic Belt from 2008 to 2020. Considering local governments' economic, innovation, talent and environmental protection competition, the paper examined the effects of local government multi-objective competition on the transfer of polluting industries in the region, and tested its spatial spillover effects. The results showed that: 1. Different competitions had different effects on the transfer of polluting industries. Economic competition intensified the transfer of polluting industries, while talent, innovation, and environmental protection competition all restrained it, among which environmental protection competition had the strongest restraining effect. 2. Compared with the transfer of polluting industries, the direction of economic competition and environmental protection competition on the transfer of industries did not change, but the degree of influence was reduced, talent competition instead promoted industrial transfer of the research region to some extent. 3. From the basin level, government competition in the upstream region more obviously intensified the transfer of polluting industries; while from the economic scale level, the restraining effect of government competition in the developed region on the transfer of polluting industries was much stronger. 4. Both innovation and environmental protection competition had positive spatial spillover effects. Therefore, it is necessary to optimize the promotion and assessment mechanism of local officials, adopt differentiated competitive constraint mechanisms in accordance with local conditions, guide local governments to transform their development concepts, promote the sharing and common use of technological innovations, and promote the orderly transfer of industries in the Yangtze River Economic Belt.

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Introduction: Drawing upon upper echelon theory and the resource-based view, this study employs a moderated mediation model to investigate the moderating role and underlying mechanisms of digital transformation in the influence of top management teams (TMT) on corporate green innovation. Methods: Our analysis of panel data from 19,155 Chinese A-share listed companies (2011-2020) demonstrates that TMT career experience heterogeneity has a positive effect on green innovation, a relationship that is further strengthened by digital transformation. Results: This study shows the role of digital transformation in amplifying the effects of TMT diversity on green innovation and the crucial role of industry-academia-research collaboration as a mediator. Heterogeneity analysis highlights that non-state-owned enterprises (non-SOEs) show more agility than state-owned enterprises (SOEs) in leveraging heterogeneous TMT to drive green innovation. Conversely, green innovation in SOEs benefits more from digital transformation, which includes both its direct and indirect effects of digital transformation. Enterprises located in non-Yangtze River Economic Belt regions benefit more from digital transformation, demonstrating the importance of a balanced distribution of digital resources. Discussion: This study provides novel insights into leveraging inclusive leadership and digital capabilities to enhance ecological sustainability. This study underscores the potential of diversified TMTs and digitalization technology integration to catalyze green innovation, which is critical for environmentally responsible transformation.

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Improving urban carbon emission efficiency (CEE) is vital to achieving the goal of urban carbon neutrality. However, the synergistic configurational effect of multiple influencing factors on CEE is not clear. Taking the Yangtze River Economic Belt (YREB) as an example, this paper adopts the standard deviation ellipse and Dagum Gini coefficient method to investigate the spatiotemporal differences in urban CEE in the YREB, and using the fuzzy-set qualitative comparative analysis (fsQCA) method, it explores the configurational effect of CEE influencing factors from the system perspective. The main conclusions are as follows: first, the overall level of urban CEE in the YREB is low, with a certain polarization phenomenon. Second, the relative differences in urban CEE in the YREB show a fluctuating upward trend, and the regional differences mainly originate from the overlapping part between regions. Finally, the main CEE influencing factors do not act in isolation, they constitute a complex process of synergistic interaction, with complementary substitution and causal asymmetry.

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Effectively utilizing water resources, which is a fundamental natural resource and a vital economic resource, directly impacts how a country's economy develops. In this study, the Super-SBM model is used to calculate the city water resource green efficiency (CWRGE) of the Yangtze River Economic Belt (YREB), 108 cities that are prefecture level or higher, from 2006 to 2021. And its temporal and spatial evolution as well as its affecting variables are examined. The results indicate that, as a whole, the YREB's CWRGE has not yet achieved an effective level. The CWRGE in the YREB generally exhibits a trend of "first decreasing and then increasing, then decreasing and then increasing" and shows a "W"-shaped evolution law, and the overall trend is upward. There are just seven cities with effective data envelopment analysis (DEA), namely Changzhou, Hangzhou, Shanghai, Xuzhou, Changde, Changsha, and Yuxi. During the reporting period, the CWRGE of cities of various scales showed significant gaps: mega cities > big cities > small and medium-sized cities. From a regional perspective, the highest rate of CWRGE was found downstream of the YREB cities, then upstream, and the middle was the lowest. Spatial correlation findings demonstrated that both the agglomeration range and the outlier range were distributed, and there were mainly two positive aggregations of space forms ("high-high (H-H) type" and "low-low (L-L) type"), and the spatial distribution changed. The results of the spatiotemporal evolution demonstrate that there are more and more cities with high efficiency, as well as cities with low efficiency. From the results of the Tobit regression model, the CWRGE in the YREB are significantly improved by the economical development level, industrial scale, and water usage structure. While foreign direct investment and environmental regulation have considerable detrimental impacts, the impact of scientific and technological investment is not significant.

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The contradiction between the basin's economic importance and its role as an ecological barrier impedes efficient urban land use. This study aims to propose an integrated approach to compare the urban land use of two representative basin areas of the Yangtze River Economic Belt and the Yellow River Basin and to investigate the impact of urban form on urban land use efficiency. Urban form was characterized by landscape indexes including Patch Density, Largest Patch Index, Edge Density, Patch Cohesion Index, and Agglomeration Index based on FRAGSTATS 4.0 software, and urban land use efficiency was measured by using Slack-Based Model-Undesirable, considering urban land becomes an emission source. Furthermore, spatial econometric models were adopted to explore direct effects and spatial spillover effects of urban form on urban land use efficiency. From 2000 to 2018, changes in urban form in both Yangtze River Economic Belt and Yellow River Basin showed increased fragmentation, enhanced heterogeneity, and more complex patch shapes. The high values of urban land use efficiency were concentrated in lower reaches of the Yangtze and Yellow Rivers. Spatial econometric models suggested that between different basins and various sized cities, the impact of urban form on urban land use efficiency had a spatial spillover effect and regional heterogeneity. Results indicated that input factors such as capital and labor should be more concentrated in metropolitan areas and urban agglomerations, thus promoting higher land use efficiency.

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The Yangtze River Economic Belt (YREB) is an important ecological barrier in China. From new perspectives, this paper explores the mechanism of high-speed rail (HSR) for green economic growth (GEG) in the YREB. This paper constructs 108 city panel data at the prefecture level and above in the YREB from 2003 to 2020. Difference-in-differences (DID) is adopted to research the impact of high-speed rail on GEG in the YREB. (1) HSR has significantly improved the GEG of the YREB. The effect value is 4.88%. The parallel trend test suggests that DID is valid. A time-varying instrumental variable combining average altitude and historical railway network is constructed for the endogeneity test. (2) Propensity score matching (PSM) and DID (PSM-DID) were employed to test the sample selection bias. (3) A battery of robustness tests, including the placebo test, variable replacement, and policy interference exclusion, is carried out. The conclusions are still valid. (4) HSR can promote the GEG of the YREB by encouraging technological innovation, industrial upgrading, and increasing ecological efficiency. The contribution rate from the largest to the smallest is ecological efficiency, industrial upgrading, and technological innovation. (5) Heterogeneity analysis shows that HSR has played an important role in encouraging GEG in the eastern, peripheral cities, and the downstream cities of the YREB. Finally, this paper puts forward policy suggestions for promoting GEG in the YREB.

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It is unidentified whether information communication technology (ICT) agglomeration can contribute to carbon reduction and to what extent it plays a role in energy conservation and emission reduction, and further exploration is urgently needed. Based on the panel data of 108 cities in the Yangtze River Economic Belt from 2008 to 2019, the spatial panel Durbin model and intermediary effect model are employed to explore the effect of ICT agglomeration on carbon emissions and its pathways. It can be indicated from the results as below. (1) The local ICT agglomeration can reduce carbon emissions, but an increase in the level of ICT agglomeration in surrounding cities will increase local carbon emissions. (2) ICT agglomeration can reduce carbon emissions through reducing energy intensity and capital mismatch. (3) The effect of ICT agglomeration on carbon emissions is heterogeneous. ICT agglomeration can suppress carbon emissions in the middle and lower reaches of the Yangtze River, while it will increase carbon emissions in the upper reaches. ICT agglomeration increases carbon emissions in old industrial cities, reduces carbon emissions in non-old industrial cities, and has a more significant emission reduction effect in non-resource-based cities. We suggest promoting the formation of a coordinated linkage mechanism for ICT industry development and carbon emission reduction policies among regions, and implement differentiated ICT development strategies according to different industrial structure types.

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