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It is an important way to realize rural revitalization and sustainable development to guide rural settlement transition (RST) in an appropriate way. This paper uses actor network theory (ANT) to construct a theoretical framework for the study of RST. Taking two typical villages with different transition paths in rural areas of North China Plain as examples, this paper reveals the mechanism of RST and makes a comparative analysis. The results show that: 1) after identifying problems and obligatory passage point, key actors recruit heterogeneous actors into the actor network by entrusting them with common interests, and realize RST under the system operation. 2) Rural settlements under different transition paths have similarities in the problems to be solved, collective actions and policy factors, but there are differences in the transition process, mechanism and effect. The actor network and mechanism of RST through the path of new rural community construction are more complex and the transition effect is more thorough. In contrast, the degree of RST of retention development path is limited if there is no resource and location advantage. 3) Based on the applicable conditions of different paths, this paper designs a logical framework of 'Situation-Structure-Behavior-Result' to scientifically guide the identification of RST paths under the background of rural revitalization. [ABSTRACT FROM AUTHOR]

With the continuous development of Internet technology, all areas of social economy have undergone profound changes. The circulation and application of data elements can significantly promote the construction of infrastructure such as big data centers and mobile base stations, and stimulate the market demand for digital consumption such as digital production, e-commerce and digital trade. Data mining technology will provide sustainable impetus for economic development. There is a clearer analysis of the role of data elements in the platform economy, but there is a lack of research in macroeconomics, especially in the coupling of finance and technology. This paper developed a coupling coordination and a coupling efficiency index system, using different methods to measure outcomes and outline the path to achieving high "quantity" and "quality" of finance-technology coupling development. Based on the data mining technology in e-commerce, the fuzzy set qualitative comparative analysis method is used to analyze the complex mechanisms and driving paths of data elements affecting the coordination degree and coupling efficiency of finance-technology coupling performance of China. We empirically document that data mining and data management are necessary to improve coupling coordination; in the absence of other conditions, data mining or data management can produce high coupling coordination, but not sufficient to improve coupling efficiency. [ABSTRACT FROM AUTHOR]

This paper aims to estimate sustainability elasticities to investigate how the sustainable development pillars in Iran should interact with those of the greatest economies in the west and east of the world, i.e., the US and China, respectively. For this estimation, this research uses SEY model including simultaneous equations system and Granger causality within 1972–2019 via two approaches of limited and full information. The results show high elasticities of sustainability among these countries, implying their considerable spillover effects and confirming the integrated sustainability perspective. In addition, the results show that the sustainability spillover effects of China are more massive than those the US on Iran sustainable development pillars. This result has two implications. The first one accepts the considerable flow of spillover effects between Iran and China. The second one shows that Iran has been unsuccessful in employing and activating the potential flows of sustainability spillover effects from the US as the greatest global economy. Therefore, policy-makers in Iran should consider a peaceful and collaborative relationship with the global community to improve and accelerate its sustainable development progress. Also, they should keep their relationship with China as the second biggest economy in the world while improving the relationship with the US to activate the potential spillover effects between the sustainability pillars of Iran and those of the US. [ABSTRACT FROM AUTHOR]

The study introduces the Five-Year Plan as an assignable Chinese experience for attaining comprehensive development to provide policy reference for goal-based development related to sustainability. Before illustrating a dynamic localized implementation path of merging the UN Development Strategy and China's national planning policies, the paper uses quantitative comparative analysis to depict an overview of this dynamic. Two key features, goal integration and development efficiency, were then built to characterize China's multidimensional development goal implementation capacity. Then, we implemented a high-dimensional fixed-effects model to examine how different stages of development impacted the likelihood of achieving our goals. [ABSTRACT FROM AUTHOR]

Strengthening the synergistic management of carbon and haze is an important means to realize China's "carbon peaking and carbon neutrality goals" and green development. In this paper, the entropy method is used to measure the key core technology innovation level of 30 provinces in China from 2011 to 2021, and the fixed-effect model is used to empirically test the impact of key core technology innovation on carbon haze synergistic governance and the internal mechanism. The study found that (1) key core technological innovation helps to promote carbon haze synergistic governance. (2) The mechanism test shows that key core technology innovation promotes the synergistic management of carbon haze by improving the clean energy structure. (3) The moderating effect shows that both market incentives and government environmental regulations will strengthen the positive relationship between key core technology innovation and carbon haze synergistic governance. The main contribution of this paper is to reveal the influence mechanism of key core technology innovation on carbon haze synergistic governance, and also to provide theoretical basis for the mechanism and law of carbon haze synergistic governance. [ABSTRACT FROM AUTHOR]

As an important way for China to achieve its dual-carbon goal, green finance has become the foundation for promoting high-quality economic development in China. In order to clarify the mechanism of green finance on carbon emissions, this paper puts green finance into the economic model and deduces the relationship between green finance and carbon emission reduction. This paper is based on the panel data of 30 provinces in China (excluding Tibet, Hong Kong, Macao, and Taiwan) from 2008 to 2019, using the individual fixed effect model, dynamical model, mediator model, and SDM model to study the impact of green finance on carbon emissions and its impact path of upgrading of the industrial structure and the development of science and technology based on the measurement of the green finance development index of each province by the entropy method. The findings show that the development of green finance can reduce carbon emission significantly, which can be sustained until at least the third phase and generates spatial spillover effects; regional heterogeneity analysis finds that the development of green finance shows geographical discrepancies: compared with the eastern and western regions, the development of green finance in central region can reduce carbon emissions more significantly; not only can the development of green finance directly reduce carbon emission, but also through the upgrading of industrial structure and technological innovation. The research not only provides a new perspective and supplementary empirical evidence for understanding the carbon emission reduction effect of green finance, but also offers some useful references for green finance to contribute to carbon emission reduction. [ABSTRACT FROM AUTHOR]

How to maintain the balanced stability and resilient development of rural systems is an important issue that needs urgent attention in the field of sustainable rural development at present. In this paper, the entropy method, spatial autocorrelation model, and Geodetector were used to explore the rural resilience level, spatial distribution characteristics, and driving factors of 31 cities in the urban agglomerations in the middle reaches of the Yangtze River (UAMRYR), and to put forward corresponding policy suggestions. The results are as follows: (1) From 2005 to 2020, rural resilience in the UAMRYR showed an upward trend with an average annual growth rate of 8.26%. The ranking of the three major urban agglomerations is Changsha-Zhuzhou-Xiangtan urban agglomerations > Wuhan urban agglomerations > Poyang Lake urban agglomerations. (2) During the study period, the spatial distribution of rural resilience gradually developed from a negative correlation to a strong positive correlation and generally showed the characteristics of high in the west and low in the east. (3) The urbanization rate, the size and structure of the economy, the difference in consumption and income between urban and rural areas, the local fiscal revenue, and the number of village committees are the key factors affecting the level of rural resilience. On this basis, we proposed policy recommendations to improve the economic, social, and ecological resilience of rural areas in the UAMRYR. The findings of this paper are expected to provide insights into the policy formulation of China's rural revitalization strategy. [ABSTRACT FROM AUTHOR]

Organization's sustainability performance is influenced by its suppliers' sustainability performance. This relationship makes sustainable supplier development a strategic competitive option for a buyer or focal organization. When considering sustainable supplier development practices (SSDPs) adoption, organizations have to balance and consider their limited financial resources and operational constraints. It becomes necessary to both select the best SSDPs set and investment allocation among the selected SSDP set such that the organization can maximize overall sustainability performance level. In this paper, an integrated formal modeling methodology using DEMATEL, the NK model, and multi-objective linear programming model is used support this objective. The proposed methodology is evaluated in a practical sustainable supply chain field study of an equipment manufacturing company in China. Through case study, we found that the interdependency among SSDPs must be considered in SSDPs selection and investment allocation problem. Theoretical, managerial and methodology implications, conclusions, and directions for future research are also presented. [ABSTRACT FROM AUTHOR]

Using basic data from China's 30 provincial regions from 2005 to 2015, the slacks-based measure of super-efficiency in data envelopment analysis (super-efficiency SBM-DEA) is used to measure industrial green economic efficiency (IGEE). Moreover, the temporal change and spatial equilibrium of IGEE are analyzed, and the panel quantile regression model (PQRM) is used to empirically analyze the impacts of the degree of agglomeration of pollution-intensive industries (PIIs) and other influencing factors on IGEE. The results reveal the following. (1) The kernel density distribution curve of China's IGEE exhibits a double-peaked distribution, and the overall peak value of the curve changes relatively greatly, exhibiting obvious spatial inequality. (2) Based on their trajectories, the centers of gravity of IGEE are all distributed in the central region. The moving speed of the centers of gravity exhibits a trend of "accelerating–decreasing–quickly accelerating." Judging from the changes of the standard deviation ellipse (SDE), the spatial distribution pattern of China's IGEE generally presents a northeast–southwest pattern, and it has exhibited the trend of shifting to a north–south pattern in recent years. (3) The agglomeration level of PIIs has a significant positive effect on the development of China's IGEE at each quantile level, and the most significant impact on China's IGEE is at the 75th quantile level. This paper empirically analyzes the impact of the agglomeration level of PIIs on IGEE to aid in the greening of industrial economic efficiency and the sustainable development of the ecological environment in China and other developing countries. [ABSTRACT FROM AUTHOR]

Environmental regulation would often limit production, causing conflicts between environmental protection and industrial development. The fundamental reason is the weak compatibility between environmental regulation goals and pig production goals. In order to improve the compatibility, this paper analysed how the herd structure adjusts the impact of environmental regulation on pig production based on the rational theory on small farmer. With the use of inter-provincial panel data from 2008 to 2020 in China, a dual moderation effect model is constructed for the empirical analysis. The results show that: (1) Strengthening environmental regulation would inhibit pig production. (2) Herb structure not only affects pig production directly, but also the nonlinear impact of environmental regulation on pig production, which would be used as a specific guideline to improve the compatibility. (3) Moderate adjustment on herb structure would help to weaken the inhibitory effect of environmental regulation on pig production and realize the sustainable development of the pig industry. [ABSTRACT FROM AUTHOR]

Sustainable development of agriculture is the basis for achieving social sustainable development. As the basic industry of national economy, green development of agriculture has become an important support for building an environment-friendly society. Agricultural fiscal expenditure is a direct channel for the government to support agriculture and promote agricultural transformation. It is important to analyze the impact of agricultural fiscal expenditure (AFE) on agricultural green total factor productivity (AGTFP) for sustainable agricultural development. Therefore, this paper employs the random effect model and spatial Durbin model to empirically analyze the direct effect and spatial spillover effect of AFE on AGTFP by using the agricultural panel data of 30 provinces in China from 2008 to 2020. Then, by taking the policy proposal as the time node, this paper also conducts a time heterogeneity analysis to measure the impact of policy enactment on AFE and AGTFP. The main conclusions are as follows: (1) AGTFP exists significant positive spatial spillover effect. The "radiation effect" of agricultural green development is significant. (2) AFE can significantly reduce the AGTFP in the local area, that is, 1% increase of AFE in the local area will reduce AGTFP by 0.037%. At present, agriculture is still yield-oriented. The improvement of AFE in the local area will lead to the expansion of local agricultural production and increase pollution emission. (3) AFE has a significant negative spatial spillover effect on AGTFP, that is, for every 1% increase in AFE, the AGTFP will decrease 0.123% in geographically similar areas, while the AGTFP will decrease by 0.116% in economically and geographically similar areas. It is obvious that AFE will promote the optimization of agricultural production conditions in the province, with the "demonstration effect" on the surrounding areas, the enthusiasm of production in the surrounding areas will increase, thus expanding the pollution emission. (4) According to the analysis of different periods, AFE has a negative impact on AGTFP mainly before the reform innovation is proposed in 2015. It indicates that reform policies have a significant impact on agricultural sustainability. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) has been highly valued as an accelerator of green economic growth. However, the difficulty in financing caused by the high investment demand and long construction cycle of high-speed rail is an ongoing dilemma facing the high-speed rail industry. Using data from Chinese cities from 2003 to 2018, this paper explores whether fiscal policy is conducive to solving financing problems for high-speed railway construction. At the same time, this paper investigates the economic and environmental benefits of high-speed rail construction investment for urban development. We find that fiscal policy helps reduce the financing cost of high-speed railway construction projects and attracts social capital, spurring investment in high-speed rail construction. When economic policy uncertainty rises, companies will choose more secure, "safe" investments to avoid potential risks, such as government-led high-speed rail construction projects, which has led to their further expansion. Regarding its economic effect, high-speed rail construction investment directly promotes urban productivity, investment scale, and industrial structure upgrades. Over the long term, investment in HSR construction helps curb urban pollutant emissions, thus contributing to urban eco-efficiency. [ABSTRACT FROM AUTHOR]

This paper empirically examines the specific impact effects and mediates transmission mechanisms of rising housing prices on urban green development using the data from 285 prefecture-level cities in China from 2010 to 2019. The results show that: 1. the rapid rise in housing prices significantly inhibits the improvement of urban green total factor productivity (GTFP) and is not conducive to promoting urban green development; 2. the effect of high housing prices on the GTFP of cities with different population size, geographical location, and resource mastery shows a significant heterogeneous effect; 3. The study of the transmission mechanism finds that soaring urban housing prices not only lead to investment distortions that weaken the overall research and innovation capacity, but also have a "solidifying lock-in" effect on the industrial structure of cities, which in turn creates obstacles to the enhancement of urban green efficiency. [ABSTRACT FROM AUTHOR]

China has abundant agricultural and forestry waste resources that are crucial sources of energy for substituting fossil fuels and achieving the carbon peaking and carbon neutrality goals. These resources play an essential role in reducing carbon dioxide emissions and promoting sustainable development. This paper presents an estimation of the number of biomass resources that can be used for energy in 2020 by using parameters such as the grass-to-grain ratio coefficient and excretion coefficient. Moreover, the potential for conversion of biomass resources into biomass energy is evaluated by using parameters such as lower heating value and gas production coefficient. Finally, based on the whole life cycle theory, the potential of biomass energy utilization to reduce carbon dioxide emissions and its impact on carbon peaking is calculated. It was found that the total amount of fossil fuels that can be replaced by biomass energy is 256 million tons of standard coal. Utilizing biomass energy can reduce carbon dioxide emissions by approximately 520 million tons, with a peak impact of 4–6% on carbon peaking. The research results presented in this article can provide valuable data to support the promotion of green transformation in various regions. The findings can serve as a useful reference for formulating localized biomass utilization plans and designing effective emission reduction policies. [ABSTRACT FROM AUTHOR]

Landscape services are an important basis for maintaining regional ecological security patterns, environmental health, and sustainable socio-economic development. As an important link between regional ecosystems and socio-economic development, micro-agents' production and life as well as their cognition and perception of landscape services notably impact the maintenance of multi-functional landscape development. This paper examines 9 rural communities in different areas and different development types in the headwater area of the Qiantang River in China, China's national key ecological functional area, in a typical case study. Based on farmer interviews and household surveys, this paper explores the changes of micro-agents' diversification perception of landscape services from 2010 to 2020. A multiple linear regression method is used to construct an index model of agents' perception of diversification of landscape services and to analyze the driving factors influencing changes. The results showed that (1) from 2010 to 2020, the micro-agent perception index of the diversity of farmland, forest, garden, and grassland landscape services increased by 0.46, 0.43, 0.67, and 0.51, respectively. Among them, the micro-agents' diversified perception of forest, farmland, garden, and grassland landscape services decreased in sequence. (2) From 2010 to 2020, in regard to the importance and vulnerability of landscape services, the difference between the perception levels of farmland landscape support services and grassland landscape regulation services in the agricultural production core area was the largest. In management and rationality perception of landscape services, the difference in the perception between grassland landscape service ecological and economic development areas was the largest. (3) Individual and family characteristics are important factors affecting the diversification perception of landscape services, while the natural environment and resource endowment impose negligible influences. Environmental policies only affect the diversification of grassland perception. The research results can provide a reference for maintaining regional landscape services, improving the well-being of micro-agents, and promoting the enhancement in ecological services and regional collaborative development. [ABSTRACT FROM AUTHOR]

Accurately assessing the susceptibility of debris flow disasters is of great significance for reducing the cost of disaster prevention and mitigation, as well as disaster losses. Machine learning (ML) models have been widely used in the susceptibility assessment of debris flow disasters. However, these models often have randomness in the selection of non-disaster data, which can lead to redundant information and poor applicability and accuracy of susceptibility evaluation results. To address this issue, this paper focuses on debris flow disasters in Yongji County, Jilin Province, China; optimizes the sampling method of non-disaster datasets in machine learning susceptibility assessment; and proposes a susceptibility prediction model that couples information value (IV) with artificial neural network (ANN) and logistic regression (LR) models. A debris flow disaster susceptibility distribution map with higher accuracy was drawn based on this model. The model's performance is evaluated using the area under the receiver operating characteristic curve (AUC), information gain ratio (IGR), and typical disaster point verification methods. The results show that the rainfall and topography were found to be decisive factors in the occurrence of debris flow disasters, and the IV-ANN model established in this study had the highest accuracy (AUC = 0.968). Compared to traditional machine learning models, the coupling model produced an increase in economic benefit of about 25% while reducing the average disaster prevention and control investment cost by about 8%. Based on model's susceptibility map, this paper proposes practical disaster prevention and control suggestions that promote sustainable development in the region, such as establishing monitoring systems and information platforms to aid disaster management. [ABSTRACT FROM AUTHOR]

As an emerging technology, industrial intelligence focus on the integration of artificial intelligence and production, which creates a new access to achieve the goal of carbon emissions reduction. Using data on provincial panel data from 2006 to 2019 in China, we empirically analyze the impact and spatial effects of industrial intelligence on industrial carbon intensity from multiple dimensions. Results show an inverse proportionality between industrial intelligence and industrial carbon intensity, and the mechanism is to promote green technology innovation. Our results remain robust after accounting for endogenous issues. Viewed from spatial effect, industrial intelligence can inhibit not only the industrial carbon intensity of the region but also the surrounding areas. More strikingly, the impact of industrial intelligence in the eastern region is more obvious than that in the central and western regions. This paper effectively complements the research on the influencing factors of industrial carbon intensity and provides a reliable empirical basis for industrial intelligence to reduce industrial carbon intensity, as well as a policy reference for the green development of the industrial sector. [ABSTRACT FROM AUTHOR]

This research focuses on the impact of the digital economy on total factor carbon productivity. Based on the panel data of China's provinces from 2009 to 2019, this paper incorporates undesired output, namely carbon emissions, into the evaluation index system, and uses the SBM-ML index to measure regional total factor carbon productivity, and uses the RAGA-PP model to measure the digital economy development index, which includes three dimensions: digital infrastructure, digital industry development, and digital economic environment. Moreover, this paper incorporates the heterogeneous threshold of technological accumulation into the framework of the impact mechanism of total factor carbon productivity and builds a threshold model to examine the impact of the digital economy on total factor carbon productivity under different technological accumulation thresholds. The research shows that, first, during the sample period, total factor carbon productivity fluctuated around the frontier, showing a certain upward trend, with significant regional heterogeneity. Second, the digital economy has a promotional effect on the total factor carbon productivity level in China and can become the new energy for the country to improve the level of green development. Third, the impact of the digital economy on total factor carbon productivity presents a significant heterogeneous threshold effect of technological accumulation, along with the increasing level of technology accumulation, the effective coefficient of the digital economy on total factor carbon productivity is increasing, and the level of significance is increasing. Last, the low-carbon driving mechanism of the digital economy has temporal and spatial heterogeneity of regional technology accumulation levels. The conclusions of this paper provide an effective reference for exploring the realization mechanism of regional total factor carbon productivity improvement, ecological civilization construction, and high-quality economic development. [ABSTRACT FROM AUTHOR]

As an ecological barrier to ensure the high-quality development of China's economy, the Yangtze River Economic Belt has attracted more and more attention from academic circles on how to promote the green development of the Yangtze River Economic Belt. This paper uses the SBM directional distance function and the Malmquist–Luenberger index to measure the green total factor productivity of 110 cities in the Yangtze River Economic Belt from 2006 to 2018, and then based on the panel threshold model to empirically explore the intensity of environmental regulations that induce trade openness and promote green total factor productivity. Studies have shown that: Firstly, trade openness has significantly inhibited the increase in green total factor productivity, but environmental regulations can play a positive regulatory role, that is increasing the intensity of environmental regulation can alleviate the adverse effects of trade openness, and it is mainly to improve the adverse effects by promoting the progress of green technology. Secondly, the results of the panel threshold model show that environmental regulations have a nonlinear regulatory effect on trade openness and green total factor productivity. When the intensity of environmental regulations crosses the second threshold, trade openness has a significant positive effect on the impact of green total factor productivity. Finally, the heterogeneity results show that in order to reverse the adverse impact of trade openness on green total factor productivity, the upper, middle and lower reaches of the Yangtze River Economic Belt should formulate relatively strict environmental regulations. [ABSTRACT FROM AUTHOR]

Accelerating efforts for the Sustainable Development Goals requires understanding their synergies and trade-offs at the national and sub-national levels, which will help identify the key hurdles and opportunities to prioritize them in an indivisible manner for a country. Here, we present the importance of the 17 goals through synergy and trade-off networks. Our results reveal that 19 provinces show the highest trade-offs in SDG13 (Combating Climate Change) or SDG5 (Gender Equality) consistent with the national level, with other 12 provinces varying. 24 provinces show the highest synergies in SDG1 (No Poverty) or SDG6 (Clean Water and Sanitation) consistent with the national level, with the remaining 7 provinces varying. These common but differentiated SDG priorities reflect that to ensure a coordinated national response, China should pay more attention to the provincial situation, so that provincial governments can formulate more targeted policies in line with their own priorities towards accelerating sustainable development. The paper reveals areas of common and differentiated SDG priority at the national and subnational levels in China considering synergy and trade-off. The findings suggest that provincial governments should formulate more targeted policy aligning with national priority to achieve SDGs. [ABSTRACT FROM AUTHOR]

In the past decades, resource shortage and environmental degradation due to rapid economic development have become a severe challenge while limiting China's regional sustainable and coordinated development. This paper provides a case study of Jiangsu Province in China employing the coupling coordination model and geo-detector model to seek solutions for realizing the region coordinated development from the interaction of technological innovation (TI ), industrial upgrading (IU ) and eco-environment (EE ). This study reaches the following conclusions. (1) The coupling coordination degree (D ) of TI - IU - EE system (TIIUEES) in Jiangsu Province was general in the stage of mild unbalance. (2) The D value exhibited a positive evolutionary trend in time series. However, the backwardness of EE constrained the regional coordination development, which led to the slow and small growth with fluctuation. (3) Spatially, the D value generally conformed to a gradient distribution from south to north, which was caused by regional internal extremely unbalanced development. (4) Economic benefits had a decisive effect on the coordinated development in TIIUEES, and the interaction of two factors could gain an "enhanced, bilinear" or even "enhanced, nonlinear" result. This study contributes to exploring the driving determinants of D value in TIIUEES based on the description of the temporal and spatial features and providing a credible reference for future research and decision-makers. [ABSTRACT FROM AUTHOR]

The free flow of factors resulting from regional integration affects not only economic and social activities between cities, but also climate and environmental changes. Under the goal of sustainable development, regional integration as a policy pathway to lower carbon intensity has rarely been clarified. In light of this, using panel data of 279 prefecture-level cities in China from 2006 to 2019, this paper treats city cluster planning as a quasi-natural experiment of regional integration and aims to discuss the impact and mechanism of regional integration on carbon intensity through difference-in-differences (DID) method, mediating effect model and moderating effect model. The following results are reached: (1) The implementation of regional integration policy effectively reduces carbon intensity, and the conclusion still holds after a series of robustness tests. (2) Total factor productivity (TFP) is the mediator of regional integration to reduce carbon intensity, and population density, technological innovation and industrial upgrading are the moderators. (3) The effect of regional integration in reducing carbon intensity varies from city location and city features. The proposed theoretical framework of regional integration affecting carbon intensity, containing mediator and moderators, not only enriches the theoretical research in the field of environment and region, but also provides a new policy path for exploring sustainable development. Therefore, it is necessary to build urban agglomerations integrating the concepts of green, low carbon, intensive and efficient. [ABSTRACT FROM AUTHOR]

Resilience is the basic attribute of rural regional systems and plays an important role in promoting rural revitalization and high-quality development. Taking 109 administrative villages in Yongchang County, Hexi Corridor, China, as evaluation units, this paper constructed a comprehensive evaluation indicator system of oasis rural resilience from ecological, economic and social dimensions, which comprehensively measures the rural resilience level. We selected typical sample zones, deeply analyzed the differences of rural resilience in "desert-oasis ecotone, oasis core area, oasis-desert-steppe ecotone" and revealed the formation mechanism, and proposed the differentiated oasis rural resilience optimization governance path. The results show that: (1) The mathematical agglomeration characteristics of oasis rural resilience are significant, mainly at high and medium levels. The ecological resilience is relatively high, followed by economic resilience, and social resilience is the lowest; (2) the spatial difference of oasis rural resilience is significant, showing the spatial characteristics of decreasing from oasis core area to oasis edge area. The rural resilience level of the three transects is the oasis core area > oasis-desert-steppe ecotone > desert-oasis ecotone; (3) ecological environment is the leading condition and core factor affecting the resilience of oasis villages. In addition, it is also affected by many factors such as the market economy and government regulation. The improvement of the resilience level of oasis villages requires multiple subjects to participate in the process of rural governance and promote the sustainable development of oasis villages according to local conditions. [ABSTRACT FROM AUTHOR]

The traditional view is that local governments are inclined to ease environmental regulations in response to fiscal pressure (FP) and alleviate FP by sacrificing the environment for economic development (ED). This paper takes Chinese Mainland resource-based cities (RBC) as the research sample but draws different conclusions. The research results are as follows: firstly, for RBC, although FP reduces environmental pollution (EP), it is not conducive to ED. Compared with non-resource-based cities (NRBC), the economic negative effect of FP in RBC is more obvious. Secondly, FP is detrimental to ED by reducing EP, and RBC have not sacrificed the environment to promote ED in the context of FP. This paper summarizes that the development path of RBC should be "optimizing government behavior → increasing FP → improving environmental quality → reducing ED level." Thirdly, the impact of FP on cities with slower economic growth and smaller economic gap is greater, and the impact of FP on cities with better environment is more obvious. This paper argues that facing FP, RBC in China will not trade EP for ED; at the same time, we suggest RBC in other countries in the face of the FP, not only thinking of promoting ED at the expense of the EP and ease the FP, but also the development of green ecological requirement, overall consideration of the relationship between EP and ED, and then achieve green and sustainable ED without degrading the environment as far as possible. [ABSTRACT FROM AUTHOR]

Taking the green credit policy in 2012 as a quasi-natural experiment, this paper uses the difference-in-differences method to explore the impact of green credit policy on enterprises' financial asset allocation and the moderating effect of government subsidy. We find that green credit policy significantly promotes the financial asset allocation of heavy-polluting enterprises, which is mainly reflected in short-term liquid financial investment, thus supporting the precautionary motivation of holding financial assets. The mechanism analysis shows that green credit policy promotes the financial asset allocation of heavy-polluting enterprises by reducing the scale of debt financing and increasing the financing cost. Government subsidy can significantly weaken the promoting effect of green credit policy on enterprises' financial asset allocation, and there is heterogeneity due to the regional environmental regulation intensity and financial development level. Further analysis shows that the negative moderating effect of government subsidy on green credit policy and enterprises' financial asset allocation significantly promotes the "shifting form virtual to real" of heavy polluting enterprises by reducing financial asset allocation. This paper discusses the impact of green credit policy on financial asset allocation of heavy-polluting enterprises in China and further clarifies the significant role of government subsidy in the process, so as to provide suggestions for government to control the "shifting from real to virtual" of enterprises. The results also provide an important reference for countries, especially developing countries, to implement green credit policy and government subsidy to achieve sustainable economic development. [ABSTRACT FROM AUTHOR]

When the incentive mechanism of green finance fails to fully promote green technology innovation in industrial enterprises, local government environmental regulations become an important tool in correcting this market failure. However, due to the "follow the cost" hypothesis, the moderating effect of the local government environmental regulation is heterogeneous. In order to explore the impact mechanism of green finance development on the efficiency of green technology innovation in industrial enterprises, spatial effects as well as the heterogeneous moderating effect of local government environmental regulation, this paper systematically evaluates the development level of green finance in 30 provinces in China from 2009 to 2019. It estimates the efficiency of green technology innovation in industrial enterprises using the super-efficiency SBM model, and empirically analyzes the impact mechanism and moderating effect using the spatial Durbin model. The results show that: (1) green finance not only positively impacts the efficiency improvement of green technology innovation in industrial enterprises but also has significant spatial spillover effects; (2) local government environmental regulation has a nonlinear "inverted U-shaped" moderating effect between the green finance development and the efficiency of green technology innovation in industrial enterprises. Based on the research conclusions, this paper proposes policy recommendations from the perspectives of deepening the regional connectivity of green finance and promoting joint regulation by local governments. [ABSTRACT FROM AUTHOR]

Free-trade zones are highlands of regional development that have a radiating effect on surrounding cities. This paper uses Yangtze River Delta Urban Agglomeration (YRDUA) data from 2003 to 2018, to examine the impact of the China (Shanghai) pilot free-trade zone (SPFTZ) on green total factor productivity (GTFP) in the YRDUA. It uses the regression discontinuity (RD) method and analyzes the influence mechanism with the help of the mediating effect model. The paper presents the following major findings. The establishment of the SPFTZ significantly promoted GTFP in the YRDUA, with technological progress being the main driving force. An analysis using the mediating effect model found that financial efficiency and industrial structure upgrading play a complete mediating role in GTFP growth in the YRDUA. Therefore, the SPFTZ should make use of its policy advantages, take full advantage of the effect of the green growth pole, and promote green mutual development with the YRDUA. [ABSTRACT FROM AUTHOR]

Energy and environmental policies are important methods for the government to restrain carbon emissions growth. Identifying the potential dynamic trends of China's carbon emissions under different scenarios has important reference significance for the government's policy implementation. This paper firstly predicted China's carbon emissions from 2017 to 2040 based on three energy transition scenarios at the industrial level. Then, Logarithmic Mean Divisia Index decomposition model was applied to evaluate the driving forces of emissions changes during 1997–2040. Finally, the Spatial–Temporal Logarithmic Mean Divisia Index model was used to explore the emissions reduction potential and the potential reduction path at provincial level. The results showed that (1) as the reduction in energy intensity cannot offset the growth of industrial scale, the carbon emissions of all industries have shown an increasing trend from 1997 to 2017; (2) In the current policies scenario, China's carbon emissions cannot reach the peak before 2040. And only in the sustainable development scenario, the carbon emissions of the three industries will all reach the peaks before 2030. And the development of non-fossil energy will reduce carbon emissions by more than 30%; (3) Hebei, Shanxi, Inner Mongolia, Ningxia, and Heilongjiang are key provinces and improving energy efficiency of the secondary industry is a potential way to promote carbon emissions reduction. The framework and main content of this paper. [ABSTRACT FROM AUTHOR]

On the basis of the "Pilot System of the Ecological Damage Compensation" launched in 2015 and a research sample of listed companies in China's heavy pollution industry from 2014 to 2017, this paper uses a difference-in-differences model to empirically evaluate the impact of the damage compensation system on corporate environmental investment, as well as the moderating effect of market degree and firm ownership. The result shows that the implementation of the damage compensation system significantly promotes corporate environmental investment and that the market degree exerts a moderating effect. The effect of supervision remains the same because of firm ownership. This research uses a pilot policy to form a natural experimental group to accurately identify the impact of environmental supervision on corporate environmental investment. The aforementioned conclusions recognize the need for the construction of the ecological damage compensation system, provide a reference for the national government to formulate specific effective environmental policies, stimulate the environmental governance motivation of regional governments, and encourage enterprises to assume environmental responsibilities and thereby achieve green sustainable development. [ABSTRACT FROM AUTHOR]

Balancing economic growth with resources and the environment to achieve sustainable development is a key issue in the development of all countries, and researchers are trying to find feasible development paths. The aim of this study is to examine the impact of human capital levels on green economic efficiency (GEE) and the underlying mechanisms in 280 prefecture-level cities in China and covering the 2003–2019 period. In addition, we calculate GEE including undesired outputs based on a super-efficiency slack-based measure (SBM) model, and we construct panel regression and moderating effect models for empirical studies. The results of the baseline regression study show that the improvement in the human capital level contributes to the GEE of prefecture-level cities. Among the control variables, the economic development level, foreign direct investment (FDI), city size, and the science and technology innovation (STI) level positively affect GEE, while industrialization and environmental regulation negatively affect GEE. The study results concerning the mechanism of action indicate that industrial structure upgrading plays a positive moderating role. That is, industrial structure upgrading can strengthen the effect of human capital on GEE, which is further clarified. This study suggests that government policies must favor the cultivation of high-level human capital, especially in the environmental protection industry, and that talent support strategies should be differentiated between regions to promote industrial structure upgrading and human capital matching through green technology development. Modern human capital theory reveals the important role of human capital in improving economic efficiency and provides new ideas for achieving sustainable development. This paper explores the role of human capital in improving the GEE based on the human capital perspective, which is important for research on the pathways to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Based on panel data from 285 Chinese prefecture-level cities from 2003 to 2020, this paper uses the difference-in-difference (DID) method to investigate the policy effect, mechanism, and heterogeneity of green finance (GF) to reduce environmental pollution. (1) Green finance has significant effect on reducing environmental pollution. The parallel trend test demonstrates that DID test results are valid. (2) Following a battery of robustness tests including instrumental variable, propensity score matching (PSM), variable substitution, and changing time-bandwidth, the conclusions are still valid. (3) Mechanism analysis reveals that green finance can reduce environmental pollution by increasing energy efficiency, adjusting industrial structure, and transforming green consumption. (4) Heterogeneity analysis proves that green finance has a substantial impact on reducing the environmental pollution in eastern and western cities, but not in central China. (5) In the "two-control zone" and "low-carbon pilot cities," the results of applying green finance policies are better, and a policy superposition effect exists. To be able to promote environmental pollution control, and green and sustainable development, this paper provides useful enlightenment for environmental pollution control for China and other similar countries. [ABSTRACT FROM AUTHOR]

Green finance has become an important reform force to promote the sustainable development of China's economy. Therefore, it has a great significance for in-depth analysis of the advantages and disadvantages of regional green finance development, to further promote it by clarifying and predicting the regional differences and dynamic evolution trends. Based on this, this paper will select the relevant index from 2001 to 2020 to construct China Green Finance Core Network (CGFCN) in different years by using Space-L method at the first, then analyze its network characteristics and spatial evolution pattern in depth, and finally predict the future development trend of CGFCN by link prediction. The research results show that: firstly, the evolution of CGFCN is mainly divided into three stages: rapid development, stable development and optimal development, and the closeness of CGFCN is constantly improving. Besides, two strong relationship networks are gradually forming, that is Beijing-Tianjin region and the Yangtze River Detla region. Secondly, with the development of green finance, the community division has changed. It is mainly divided into four communities, named the Beijing-Tianjin-Hebei leading community, the eastern provincial community, the Yangtze River Delta community and the central and southern joint community. Different communities will have different integration in different periods. Thirdly, the future development direction of green finance network is mainly Beijing-Tianjin-Hebei region and Yangtze River Delta regions, and their outward radiation are mainly shown in the eastern coastal and central regions, which also have strong development potential. In this regard, it is proposed to coordinate development across provinces to speed up the "urban integration" of green finance services; Establish an efficient community development mechanism and promote the interconnection of green finance markets and infrastructure between different regions; Strengthen the resource flow among regions and coordinate the resource competition of green finance. [ABSTRACT FROM AUTHOR]

With carbon emissions becoming more and more closely related to human activities and China being the world's largest emitter of carbon dioxide, the cost of environmental quality deterioration is high and environmental sustainability is low. Against this background, it is urgent to implement low-carbon recycling and green development by introducing green funds based on the role of environmental regulation intensity. Therefore, based on the data of 30 provinces from 2004 to 2019, the paper considers the dynamic impact of environmental regulation intensity and green finance development on regional environmental sustainability. The provincial data involve specific spatial locations and focus on the economic interactions among provinces, and the spatial econometric model is very applicable. Based on the spatial econometric model, this paper empirically examines the direct effect, spatial spillover effect, and total effect, considering both spatial and temporal patterns. The research shows that (1) China's provincial environmental sustainability shows a noticeable spatial agglomeration effect, which is significantly and spatially autocorrelated and clustered. (2) Based on the national level, an increase in the intensity of environmental regulation will significantly increase regional environmental sustainability, and the development of green finance will also significantly increase regional environmental sustainability. Additionally, the environmental regulation intensity has a significant positive spatial spillover effect, which may increase environmental sustainability in neighboring provinces. There is also a significant positive spatial spillover effect of the impact of green finance development on environmental sustainability. (3) Based on the provincial level, the impact of environmental regulation and green financial development on environmental sustainability in each region is significantly positive, with the most significant impact in the western region and the smallest coefficient in the eastern region. The paper proposes policy and managerial implications to promote regional environmental sustainability based on the above findings. [ABSTRACT FROM AUTHOR]

The current study developed a systematic analytical framework to explore the logic of forming the cohort effect of green governance and green development in China in the new era. Based on provincial panel data from 2008 to 2018, this paper examines the existence, scope, and induced control of the green governance peer effects using a spatial econometric approach. The study found that the following: (1) Influenced by the top-level design of the central government and the contradictory governance of regional development, the local governments form the peer effects in green governance activities. The existence of spatial relationships makes local governments dependent on a solid financial support system and a basis for industrial transformation, thus counteracting regional competition for green governance. (2) The green governance peer effects tend to decay with increasing geographical distance but do not disappear across regional boundaries under either spatial interaction framework. (3) Considering the impact of green governance policy systems and regional heterogeneity, the green governance peer effects decrease in the eastern, western, and central regions in that order. (4) Further, the influencing factors show that the green governance peer effects arise from intra-local government competition under the decentralization of power between the central and local governments. The competition for scales and the relative performance appraisal system reinforces the peer motivation of each subject. (5) The strong correlation of green governance willingness indicates that local governments cannot escape from will-led emotional behavior, and personal interests and governance motivation further drive the formation of pseudo-rational decisions, ultimately leading to irrational group decisions. [ABSTRACT FROM AUTHOR]

Environmental resources play an extremely important role in economic development. In the context of China's economic development entering a new normal, attaching importance to environmental protection and strengthening environmental regulations will have an important impact on the original foreign direct investment (FDI) and China's economic development. Therefore, this paper combines the characteristics of the "new normal" of China's economic development, takes 30 provinces in China from 2008 to 2017 as the research object, and uses the PVAR model and impulse response function to re-verify the interaction mechanism and path among environmental regulation, FDI and high-quality economic development. The study found that: (1) There is an obvious mutual promotion relationship between environmental regulations and the quality of China's economic development and economic development environment. Strengthening environmental regulation is conducive to the realization of China's economic "new normal" development goal. (2) Although the strengthening of environmental regulation will have a significant constraint effect on FDI and China's economic growth rate, but the effect is relatively small. (3) FDI and economic growth rate variables are mutually motivated and promote each other, but both of them have a significant inhibitory effect on regional environmental regulation. In general, under the background of the "new normal" of China's economic development, appropriately increasing the intensity of environmental regulation is not only conducive to environmental protection and promoting high-quality and sustainable economic development, but also can serve the purpose of guiding the structure of foreign investment and transforming the mode of economic growth. [ABSTRACT FROM AUTHOR]

Industry is a core area to achieve the carbon neutrality target for most developing countries including China. Hence, it is of great practical significance to study the spatio-temporal characteristics of China's industrial carbon intensity and its evolution. The exploratory spatial data analysis methods were adopted to conduct global and local spatial correlation analysis in this paper. The result shows that (1) the industrial carbon emission intensity decreases year by year, with high industrial carbon emission intensity in the West and low in the East. (2) There is a correlation in the spatial distribution of industrial carbon intensity, with the Moran index experiencing the stage of descending first and then ascending. (3) The local spatial clustering of industrial carbon intensity is obvious. (4) Half of the provinces have experienced a leap, with the majority located in the western part of China. Based on these findings, it is concluded that industrial emission reduction policy synergy between provinces is particularly important, such as low-carbon industrial production policy and green industry development policy. [ABSTRACT FROM AUTHOR]

There is a relative dearth of empirical studies quantitatively analyzing the implementation effect of green finance reform and innovation pilot zones (GFRIs) on green innovation at the micro-enterprise level. Thus, this paper aims to construct the difference-in-difference-in-difference method to explore the influence of Chinese GFRIs on corporate green innovation of heavy-polluting enterprises based on green patent data. Results show that the pilot policy has significantly decreased green patents of heavy-polluting enterprises by approximately 42.64%, indicating that the policy has a significant innovation inhibition effect and fails to exert the Porter effect. Furthermore, establishing GFRIs has a more effective inhibition effect on the green invention patent than the green utility model patent. Moreover, although enterprises of different scales have different innovation capabilities, the negative impact of GFRIs on green innovation of heavy-polluting enterprises is widespread. Still, the negative impact is more pronounced for big-scale enterprises. The above empirical evidence is essential in formulating green finance development strategies and promoting green economic transformation. [ABSTRACT FROM AUTHOR]

Green innovation is an essential support for environmentally sustainable development. However, little attention has been given to the impact of financial expansion on green innovation in the existing literature, and there is a lack of studies based on the perspective of the financial geographical supply structure. This study uses latitude and longitude information to construct firm-level financial geo-density data in China. It examines the impact of financial geo-density on a firm's green innovation and mechanisms. The results reveal that as financial geo-density increases, green innovation quantity increases, but green innovation quality decreases. The findings of the mechanism test indicate that an increase in financial geo-density decreases the cost of financing and boosts bank competition in the vicinity of the firm, hence resulting in a rise in the firms' green innovation quantity. Nevertheless, the degree of bank competition increased by financial geo-density increase negatively affects firms' green innovation quality. Heterogeneity analysis shows that financial geo-density has a more significant positive impact on a firm's green innovation quantity in high environmental regulation areas and high-pollution industries. Firms with low innovation capabilities are the main group responsible for the decline in green innovation quality. For firms located in low environmental regulation areas and medium- to light-pollution industries, financial geo-density has a more significant inhibition effect on green innovation quality. Further tests have shown that the extent to which financial geo-density enhances a firm's green innovation quantity diminishes as market segmentation increases. A new concept of financial development policies based on green development and innovation is presented in this paper for developing economies. [ABSTRACT FROM AUTHOR]

The transition from traditional logistics to green and low-carbon logistics is crucial and inevitable due to the pressure of climate change and sustainable development in China. Meanwhile, technological innovation is perceived as an important factor affecting the development of the logistics industry. To explore the impacts of technological innovation and other factors and to propose proper policies based on the results, this study utilizes a generalized estimating equations (GEE) regression model to analyze panel data of 30 provinces during 2001–2019. Firstly, the entropy weight method is applied to calculate the green logistics development level based on an index system considering green factors. Secondly, a GEE model which considers the correlation among different observations is used to investigate the impacts of crucial factors on the green logistics development level. Moreover, regional heterogeneity is also analyzed in this paper by comparing the regression results of the Eastern region, Central region, and Western region. Based on the above analysis, several conclusions are drawn: (1) In terms of the average green logistics development levels, the Eastern region ranks 1st, the Central region ranks 2nd, and the Western region ranks 3rd. (2) GEE regression model is proved effective in our sample. (3) For the full sample, technological innovation, trade openness, and logistics infrastructure positively affect the green logistics development level; while, government regulation and energy intensity negatively influence the green logistics development level. (4) Regional heterogeneity is confirmed in our sample. Related policy recommendations are proposed based on our regional regression results. Take the Eastern region as an example, the local governments in the Eastern region should upgrade the manufacturing industry, reduce government financial investment in the transportation sector, and enhance environmental control expenditure in the transportation sector. [ABSTRACT FROM AUTHOR]

Building livable rural regions is a key objective of China's rural revitalization, and fostering coordinated and sustainable regional development in China necessitates investigating the geographical and temporal distribution and influencing variables of livability in China's rural areas. This paper compares the concept and connotation of rural livability based on regional economic development theory and sustainable development theory, integrates China's rural revitalization strategy, proposes an index system for evaluating rural livability in China, and conducts an empirical analysis of livable rural areas. Firstly, the level of rural livability development is measured by the entropy method; secondly, the aggregation effect of provinces is demonstrated by using the Moran I index, and finally, the spatial Durbin model is used to explore the influencing factors of rural livability and its spatial spillover effects. Findings of our study reveal that the results of the entropy method indicate that the livability of rural China is in a growing development trend in all provinces, but the livability shows some regional disparities. The Moran index reveals that there are obvious spatial autocorrelations in the livability of Chinese rural areas, and the most typical features are the "high" and "low" clusters. The spatial Durbin model suggests that the influences on the development of rural livability are diverse. Besides, other variables such as environmental pollution and per capita housing area show a negative association with rural livability, and investment in fixed assets, cultural atmosphere and medical health show a positive relationship with rural livability. Based on the study findings, it is proposed that in the rural revitalization strategy process, the formulation of monitoring system should be strengthened and intensify the promotion of coordinated inter-regional development. [ABSTRACT FROM AUTHOR]

In order to test the impact of green finance on the low-carbon development level of China's manufacturing industry, this paper takes green finance as an explanatory variable, and chooses the level of fixed asset investment in the manufacturing industry, the intensity of environmental regulations, the proportion of environmental pollution control investment, and the proportion of R&D investment as four control variables. Empirical tests are carried out on the four dependent variables, including manufacturing industry's low-carbon development level, added value growth rate, industrial structure upgrading level, and environmental protection status. The test results show that green finance is positively correlated with the low-carbon development of the manufacturing industry and the growth rate of added value, and inversely correlated with industrial structure upgrading and environmental protection; green finance supports dependent variables in the following order: low-carbon development > environmental protection > economic growth > industrial structure. It can be seen that the main role of green finance is to promote low-carbon development and environmental protection, but it is not the best tool to promote the growth rate of manufacturing industry and upgrade the level of industrial structure. In addition, due to the spillover effect of green finance in the process of promoting the development of the manufacturing industry, it is necessary to increase green financial investment in a long-term and sustained manner to gradually promote the low-carbon and sustainable development of China's manufacturing industry. [ABSTRACT FROM AUTHOR]

Agglomeration of the industry significantly impacts economic performance and environmental sustainability. In line with its strategic context of striving to achieve carbon reduction targets, China is making efforts to optimize the producer services landscape to reduce carbon emissions. Understanding the spatial correlation between industrial agglomeration and carbon emissions is particularly crucial against this background. Based on POI and remote sensing data of China's Yangtze River Economic Belt (YREB), the paper adopts the mean nearest neighbor analysis, kernel density analysis, and standard deviation ellipse to portray the agglomeration of producer services. Then uses Moran's I to present the spatial distribution characteristics of carbon emissions. Accordingly, the spatial heterogeneity of producer services agglomeration and carbon emissions is showed using the Geographic detector so as to provide strong support for industrial structure optimization and sustainable development. Here are some of the conclusions drawn from the study: (1) Producer services are a significant state of agglomeration in the provincial capitals and some central cities, with similar agglomeration patterns. (2) Carbon emissions exhibits significant spatial aggregation characteristics, with the spatial distribution pattern of "High west–Low east". (3) Wholesale and retail services industry is the primary risk factor that causes spatial differentiation of carbon emission intensity, "leasing and business services industry-wholesale and retail services industry" is the key interaction factor of the spatial differentiation. (4) Carbon emissions shows a downward trend followed by an upward trend as producer services agglomeration increases. [ABSTRACT FROM AUTHOR]

It will contribute to ameliorating the national carbon trading system and further benefit the realization of China's carbon peaking and carbon neutrality goals through in-depth study and summarize the effectiveness of carbon trading policy implementation in pilot areas. Based on the multi-phase difference-in-differences approach and synthetic control method, this paper utilizes China's provincial panel data from 2006 to 2020 to comprehensively assess the Porter effect (including the economic and green innovation effects) and carbon mitigation effect of carbon trading policy from the overall and local perspectives. Then the robustness test and mechanism analysis are carried out. The findings show that: (1) from the overall effect, the carbon trading policy brings a noticeable carbon mitigation effect and Porter effect, and the intensity of the impact keeps changing over time; (2) there is significant heterogeneity in the local effects of this policy on the eight pilot provinces and cities, with only Chongqing obtaining both the Porter effect and the carbon mitigation effect, while the rest of the regions do not yield the triple dividend of economic, environmental, and green innovation simultaneously; (3) there are much more prominent environment and green innovation effects in the developed regions, while the underdeveloped ones have better economic development and no green innovation effect; (4) the policy can bring environmental and economic dividends through energy structure optimization. However, due to the carbon rebound effect, stimulating green innovation pathways can only boost the economy while carbon emissions increase instead. The research conclusions can provide the decision support and policy direction for policies related to China's carbon market. [ABSTRACT FROM AUTHOR]

China's power sector must cut its carbon emissions by 90% by 2060 to become carbon neutral. Green finance, as a crucial link in sustainable development, is garnering attention for its role as a mechanism for the green transformation of power enterprises. The process of green transformation development is highly challenging and requires a lot of financial support. This paper discusses the design of schemes for fiscal and financial support mechanisms for the green transformation of power enterprises, financing mechanisms to strengthen green finance, and financial support mechanisms to promote carbon trading. The utilization of green finance by power enterprises is assessed after defining the impact routes of green finance on clean energy power firms and highly polluting power firms. Using the SBM-GML model with variable returns to scale, the dynamic change of the use efficiency of green finance in power enterprises is calculated. At the same time, the enterprises are classified by power generation methods, and the changes in the power generation structure of power enterprises are analyzed. Compared with 2014, the total power generation in 2021 increased by 59.14%, wind power generation increased by 170.78%, and photovoltaic power generation increased by 974.31%. Hydropower, by contrast, grew by 94.14% and thermal power by only 45.09%. The results show that the evolution of total factor productivity and green total factor productivity of the 24 listed electric power enterprises is "M" shaped, that the main cause of the fluctuation is the serious phenomenon of "Triple Abandonments" of wind, light, and water in China's power industry, and that the main means to improve total factor productivity and green total factor productivity of the power industry is to improve green power production technology. Classified by power generation mode, it is found that hybrid power generation enterprises have the highest average efficiency value, followed by wind power generation. China's power enterprises are still dominated by thermal power generation; before the "Double Carbon" target, green power generation enterprises have not significantly improved the efficiency of green finance. The series of green finance mechanisms of action described in this study have a beneficial impact on the green transition of energy, according to a predictive analysis that combines existing policy objectives and practical mechanisms. Even without green financial support, the composition of China's major clean energy sources will account for 86.85% of total electricity generation by 2060, while with green financial support, coal generation will fall to 0% around 2056, with hydroelectric, wind, and photovoltaic generation accounting for 11.81%, 50.00%, and 38.19% of electricity sources, respectively, and green finance will drive important technological changes, and the "Triple Abandonments" phenomenon will be fundamentally corrected. Finally, countermeasures and suggestions for the healthy development of green finance in power enterprises are proposed based on the findings of the study. [ABSTRACT FROM AUTHOR]

As a noteworthy initiative of financial supply-side reform to precisely support the green development system, can green finance (GF) help achieve the dual goals of "carbon peaking" and "carbon neutrality"? Using data from China's provincial panel between 2007 and 2019, this paper measured the green finance index by the entropy method and the carbon emission efficiency (CEE) with carbon emission as the non-desired output by the Super-SBM model. Then, the influence of GF on CEE was empirically investigated by the dynamic panel model and the spatial Durbin model. The findings show that GF can significantly improve CEE and has a positive spillover impact on CEE in provinces with close economic ties; the upgrading of the industrial structure is a key mediator in the transmission of GF to CEE; and regional heterogeneity analysis finds that GF notably improves CEE in eastern, high development levels of economic and GF regions. The research can offer some theoretical and empirical references for green finance to contribute to low-carbon economic growth. [ABSTRACT FROM AUTHOR]

The sustainable development of China's economy is bottlenecked by resource shortage and environmental pollution. As the leading resource consumer and pollutant source, the industrial sector needs to improve its energy efficiency. This paper establishes a super epsilon-based measure (Super-EBM) model with bad outputs like environmental cost and evaluates the industrial green total-factor energy efficiencies (IGTFEEs) of 30 provinces in China during 2000–2017. Unlike previous research, the main contribution of this paper is to choose four environmental pollutants as bad outputs (industrial carbon dioxide, industrial sulfur dioxide, industrial chemical oxygen demand, industrial solid waste). By contrast, the previous studies mostly only take one environmental pollutant as bad output, i.e., the bad outputs are not fully measured. Then, the spatiotemporal dynamics and spatial correlations of the IGTFEEs were analyzed, and the influencing factors of IGTFEE were examined empirically with a spatial econometric model. Finally, this paper adopts generalized method of moments (GMM) to solve the endogenous problem, trying to assure the robustness of estimation results. The results show significant provincial differences in IGTFEE. Most eastern coastal provinces achieved satisfactory IGTFEEs, while most inland provinces had undesirable IGTFEEs. Eastern region achieved the highest IGTFEE, followed by central region; western region had the lowest IGTFEE. The IGTFEE improved over time in some provinces while worsened greatly in some provinces. The IGTFEE in most provinces need to be further improved. Global Moran's I values indicate that the provincial IGTFEEs were clustered in space, rather than randomly distributed. Local indication of spatial association (LISA) map reflects significant local spatial clustering of provincial IGTFEEs. In addition, IGTFEE is significantly promoted by industrial structure, technological innovation, human capital, opening-up, and energy structure yet significantly suppressed by ownership structure and environmental regulation. Considering the endogeneity, GMM results show that the estimation results of the model were robust. Specific policy recommendations include vigorously developing high-tech industries, deepening state-owned enterprises reform, diverting more funds to research and development, cultivating versatile talents, introducing environmentally-friendly foreign capital, accelerating the implementation of clean energy development strategy, and widening the fund channels of pollution control investment. [ABSTRACT FROM AUTHOR]

China, as the world's largest energy consumer, has made the green economy a central component of its economic development strategy. However, how to effectively play the government's crucial role in promoting the development of the green economy has become the focus of research by a significant number of economic experts. This paper uses the Super-SBM model to measure the green economy development index by introducing carbon dioxide emissions and industrial "three wastes" emissions and analyzes the relationship between fiscal decentralization, green technology innovation, and the green economy from the vantage point of local government behavior. It is discovered that fiscal decentralization significantly inhibits the development of the green economy, and local green technology innovation activities in the last period will amplify this negative impact. The above findings pass the robustness test. After introducing comparative analysis of economic growth indicators that are measured by the stochastic frontier analysis (SFA), the results show that only in the eastern region does fiscal decentralization both drive economic growth and do not inhibit green economy development by local government officials' political promotion motives and self-interested preferred expenditures, but overall economic promotion and green economy inhibition caused by fiscal decentralization exist simultaneously in the Yangtze River Economic Belt region, and significant heterogeneity differences exist in the rest of the regions. The findings suggest that regulating local government fiscal behavior and improving fiscal transparency are very important to promote the development of China's green economy. [ABSTRACT FROM AUTHOR]

There is no conclusion on whether green development can symbiotically coexist with shared development, and the effect of environmental protection tax on labor share provides new evidence to answer this question. This paper presents a theoretical analysis of change in labor share in the exogenous impact of the enforcement of the Environmental Protection Tax Law of China, and proposes relevant hypotheses. At the same time, empirical data of listed firms on the main board from 2013 to 2019 are collected. A difference-in-differences model is constructed to test the hypotheses empirically. The study found that the reform of environmental protection fee to tax reduced the labor share of high-polluting firms by an average of about 1.43%. However, it did not significantly reduce the share of corporate executives' income. The reform of environmental protection fee to tax reduces the labor share of high-polluting firms through the crowding-out effect and the substitution effect of production technology. The heterogeneity study revealed that the reform of environmental protection fee to tax has more substantial negative impacts on firms with high financing constraints, low market concerns, and low government subsidies. There is no significant difference between the impact on state-owned and private firms. The reform of environmental protection fee to tax has a more substantial negative impact on the firms in Central and Western China than those in more economically developed Eastern China. [ABSTRACT FROM AUTHOR]

Industrial structure low-carbon restructuring is an essential channel to accelerate China's economic growth and fulfilling carbon emission reduction goals. Whether carbon emission trading pilot policy, as an influential carbon reduction instrument, fosters industrial structure low-carbon restructuring is of major significance to green economic development. This paper empirically investigates the shock of the carbon emission trading pilot policy on industrial structure low-carbon restructuring using the differences-in-differences (DID) and synthetic control method (SCM). Statistics reveal that sectors with low carbon productivity, such as electricity, steam, and hot water production and supply, ferrous metal smelting and pressing, etc., and sectors with high carbon productivity, such as electrical equipment and machinery, electronics and telecommunication equipment, etc. The industrial structure did not develop a stable trend of change before the 12th Five-Year Plan, but a stable trend of low-carbon restructuring emerged after such a period. Carbon emission trading pilot policy significantly facilitates industrial structural low-carbon restructuring. Carbon emission trading pilot policy inhibits energy-intensive industries in the industrial sector significantly, which promotes industrial structure low-carbon restructuring. Therefore, policymakers need to develop a nationwide carbon emission trading market that includes more industries to guide production factors to industrial sectors with high carbon productivity for industrial restructuring and dual carbon goals. [ABSTRACT FROM AUTHOR]

Climate change exacerbates uncertainties in water resource management, water supply, and treatment that are energy intensive and then exert great pressure on climate change mitigation; hence, interrelated and contradictory characteristics within the water-climate change (WC) nexus system are needed to be studied. The nexus thinking and coordination of WC would impact many realistic practices and assist in sustainable socioeconomic development since traditional single-target policies have sometimes been out of function. Hence, the ability to direct water production and use as well as climate change mitigation has become a hotspot recently. Furthermore, we find that there has been no complete research on reviewing the impacts of the WC nexus in different areas on the Sustainable Development Goals (SDGs). Hence, this paper builds a core nexus of WC and then analyzes those effects on social and environmental aspects in many areas, including sewage treatment, energy transition, waste treatment, land management, and ocean management. This paper discusses how WC interlinkages are utilized to realize SDGs in those areas. Moreover, uncertainties derived from exogenous hydrology, climate change, and anthropogenic endogenous systems for realistic problems appeal to gradually increasing concern. Finally, implications offer valuable guidelines for integrated management of water and carbon emissions, as well as sustainable socioeconomic development in the future. [ABSTRACT FROM AUTHOR]