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This paper investigates how digital finance alleviates the resource curse effect from resource-based cities in China. This paper selects the data from 88 resource-based cities in China from 2011 to 2019 to construct the econometric model test hypothesis. The results show that (1) a resource curse does exist in Chinese resource-based cities. (2) Digital finance can alleviate the resource curse of resource-based cities in China, and this effect has two significant thresholds. (3) The heterogeneity test results show that digital finance's mitigation effect on the resource curse significantly differs in cities with different environmental regulation intensities and resource abundance. (4) Using the implementation of the broadband China strategy as the proxy variable of digital finance for the robustness test, the above conclusions are still robust. This paper considers the impact of digital upgrading on the financial industry and further studies the mitigation effect of digital finance on the resource curse. It provides a new perspective to study the recent changes in traditional issues in the digital era. [ABSTRACT FROM AUTHOR]

Green finance can promote economic transformation and technological innovation and play a key role in solving the ecological environment and energy crisis. This paper constructs a comprehensive ecological livable environment evaluation system based on the provincial panel data in China from 2011 to 2019. At the same time, the panel mediation effect and spatial econometric model are used to test the impact of green finance on the ecological and livable environment. The main research conclusions include the following: (1) green finance has significantly improved China's ecological and livable environment; (2) green finance improves the ecological and livable environment by improving the level of technological innovation; (3) the impact of green finance on the ecological livable environment has regional heterogeneity, and green finance in the central provinces has a better effect on the improvement of the ecological livable environment; and (4) the ecological livable environment among Chinese provinces has a significant positive spatial correlation. Among them, green finance has significantly improved the local ecological livable environment but reduced the ecological livable environment of surrounding provinces. Based on the above conclusions, this paper suggests that the government should pay more attention to green finance and technological innovation and coordinate the development of the ecological livable environment among provinces. The research results provide empirical evidence for better developing green finance and improving the ecological livable environment and also provide certain theoretical guidance for China's coordinated regional development and high-quality economic development. [ABSTRACT FROM AUTHOR]

The economic and technological development zone (ETDZ) serves an essential role in driving green development and ecological civilization. Therefore, it is crucial to investigate the impact of ETDZs on eco-efficiency for sustainable development. This paper investigates the impact of the establishment of ETDZs on eco-efficiency by constructing a differences-in-differences (DID) model on the basis of 253 cities in China from 2004 to 2017 as the dataset. This paper also explores the possible intrinsic impact mechanisms through the channels of industrial structure and technological innovation by constructing a mediating effect model, and the heterogeneous effects of ETDZs on eco-efficiency from the perspectives of regional imbalance and city class heterogeneity. Statistical results report that ETDZs significantly positively affect eco-efficiency and such effects are most significant in the first year after the establishment of ETDZs. Industrial structure upgrading and technological innovation are essential role mechanisms for ETDZs to enhance eco-efficiency. Besides, the enhancement effect of ETDZs on eco-efficiency is only observed in the eastern part of the city, with an insignificant inhibitory effect in central and western parts of the cities. However, the establishment of ETDZs in cities with higher city classes is more beneficial to improve eco-efficiency. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) is becoming increasingly important in the field of corporate sustainability. However, little literature has focused on the relationship between CSR and corporate carbon emissions in developing countries. This paper aims to fill this gap by exploring the relationship between CSR and corporate carbon intensity from the perspective of financing constraints. We examine the mediating effects of financing constraints using a mediating effects model by using Chinese listed companies data from 2011 to 2019. The analysis results of this paper are as follows: (1) CSR can reduce corporate carbon intensity. (2) Financing constraints have a positive mediating role between the two. Namely, CSR can reduce the financing difficulties of enterprises, and enhance carbon–neutral capacity. (3) The carbon emission reduction effect of CSR is different in different life cycles. (4) CSR has a greater impact on the carbon intensity of state-owned enterprises, high-tech enterprises, and heavy polluting enterprises. These facts provide meaningful references for developing countries such as China to promote CSR and carbon governance. [ABSTRACT FROM AUTHOR]

Resource-based cities, which are widely distributed in China, contribute significantly to China's sustainable development. The digital economy and the construction of ecological civilization are central issues in the sustainable development of resource-based cities, and it is necessary to analyze the impact of the digital economy on the ecological resilience of resource-based cities. Thus, this paper measures ecological resilience of 117 resource-based cities from 2011 to 2020 using the entropy weight TOPSIS (technique for order preference by similarity to ideal solution; see Table 1 for a list of acronyms) method and empirically investigates the impact and mechanism of digital economy on ecological resilience using the spatial Durbin model (SDM) and intermediary effect model. The results show that the ecological resilience of resource-based cities has a certain upward trend, with a stepwise distribution pattern from east to west. There is a significant positive correlation between ecological resilience of resource-based cities, showing the phenomenon of club convergence which is primarily dominated by high-high (H–H) and low-low (L-L). The digital economy has a significant spatial spillover effect, which promotes ecological resilience of resource-based cities in the local and adjacent regions. A mechanism analysis reveals that technological innovation and industrial structure are mediators between digital economy and ecological resilience of resource-based cities, with significant heterogeneity in region and growth cycle. Among them, the intermediary role of technological innovation is stronger. Following the above findings, this paper proposes policy suggestions related to digital economy evolution and ecological resilience enhancement. This paper further enriches the literature on the ecological resilience and provides a theoretical basis for government policy-making. [ABSTRACT FROM AUTHOR]

Air pollution and urban innovation are two important issues that have accompanied China's economic growth in the past decade. Based on the quasi-natural experiment of central heating in northern China in winter, this paper uses regression discontinuity design (RDD) to isolate the causal relationship between air pollution and urban innovation in China by matching urban data with multiple micro databases. Further, the possible influencing mechanism is discussed from the perspective of human capital. The results show that—air pollution significantly inhibits urban innovation—specifically, a 1% increase in air pollution significantly reduces urban innovation by 1.463%; compared with non-invention patents, air pollution has a more obvious inhibitory effect on invention patents with higher innovation capacity requirements and technology content. In terms of the impact mechanism, air pollution may undermine urban innovation by impairing healthy human capital and increasing the emigration of high-level human capital from cities. [ABSTRACT FROM AUTHOR]

The deteriorating global environment has attracted wide attention in various countries. How to curb environmental pollution and achieve sustainable economic growth has become an urgent problem that we must face. As an effective tool for pollution control, environmental tax has been implemented in many developed countries and has achieved good results. As the largest developing country in the world, China introduced the first environmental tax law in its history in December 2016, which is regarded as a major reform of the green tax system. To explore the implementation effect of environmental tax in China, this paper takes 3867 Chinese listed enterprises (2015–2020) in Shanghai and Shenzhen A shares as the research sample and explores the microeconomic effect of environmental tax reform using the difference in difference (DID) method. It is concluded that the environmental tax reform can produce a positive impact on the corporate profit margins while curbing the enterprise pollution behavior. This positive effect comes from the investment improvement effect and the cost-saving effect, and this effect is heterogeneous between different regions and property rights enterprises. Therefore, the design of the tax system must be implemented with different measures. Environmental taxes have achieved positive policy results in China, contributing to sustainable economic growth. This tax reform has an important reference value for the developing countries in the industrialization stage. [ABSTRACT FROM AUTHOR]

Revealing the general laws of land use transformation (LUT) under the coupling evolution of different socio-economic and eco-environment (SE-EE) in mountainous areas is of great significance for rational use of land resources, regional socio-economic development, and eco-environment protection. This paper constructs a research framework of LUT under the coupling evolution of SE-EE and takes Fengjie County as an example to conduct a case study. The results show (1) the socio-economic development level and eco-environment quality showed an overall growth trend from 2000 to 2020, showed the distribution pattern of high in the Yangtze River valley and low in the mountainous areas, and low in the Yangtze River valley and high in the mountainous areas respectively. (2) The coupling evolution of SE-EE showed five types: synchronous development of SE-EE, socio-economic development and ecological retarded, socio-economic retarded and ecological restoration, low socio-economic development level, and low eco-environment quality. (3) The transformation of land use quantity, structure, and function corresponded to the coupling evolution of SE-EE. Cultivated land was reduced when the socio-economic development level was relatively high, and the function changed from production to ecological and eco-economic. When the eco-environment quality was high, cultivated land was reduced, and the function changed from production to ecological. (4) The framework constructed in this paper is universal to the mountainous areas represented by the Three Gorges Reservoir Area (TGRA) and the plain areas where the LUT and SE-EE evolution are different from the mountainous areas. [ABSTRACT FROM AUTHOR]

More and more emphasis is placed on the common development of economy and ecological environment in China's development strategy, and one of the key solution is green technology innovation of enterprises. This paper takes the carbon emission trading scheme carried out in China in 2013 as a quasi-natural experiment and uses the data of China's A-share non-financial listed companies and the DID method to empirically test the impact of the scheme on enterprise green technology innovation from the micro level. The results suggest that the carbon emission trading scheme has a significant role in promoting enterprise green technology innovation, mainly through the innovation of green practical patents and alternative energy-based patent. Using a series of robustness tests such as dynamic effect test, placebo test, and PSM-DID, it is found that the results are still valid. Further analysis finds that debt financing will weaken the role of carbon emission trading scheme in promoting enterprise green technology innovation. And the carbon emission trading scheme plays a greater role in promoting green technology innovation in state-owned enterprises, enterprises belonging to areas with strong pollution control intensity and high pollution industry. [ABSTRACT FROM AUTHOR]

As a kind of enterprises most affected by green policies—heavily polluting enterprises, whether the government's relevant policies can achieve its policy goals and what impact will be exerted on such enterprises is a critical issue. Based on the data of listed heavily polluting enterprises in China from 2007 to 2020, this paper uses the difference in differences model to test the impact of green credit policies on the liquidity risk of heavily polluting enterprises. The results show that the green credit policies intensify the liquidity risk of heavily polluting enterprises. Moreover, the green credit policies increase the financial and stock liquidity risks of heavily polluting enterprises by reducing the long-term debt ratio and information transparency. Green innovation and equity balance weaken the positive impact of green credit policies on the liquidity risk of heavily polluting enterprises. Heavily polluting enterprises can reduce the impact of green credit policies on their liquidity risk by increasing investment in green innovation and improving ownership structure. [ABSTRACT FROM AUTHOR]

To cope with global climate change and energy security, the realization of the low-carbon energy transition has become an inevitable choice for international carbon emission reduction requirements and energy structure adjustment. Vigorously developing renewable energy has become an essential part of energy policies in many countries. Under the incentive and guidance of renewable energy industry policy, China's renewable energy has developed rapidly, and energy structure has been optimized. However, many problems have been exposed. Can China's renewable energy industry policy effectively support low-carbon energy transition? This paper uses the method of theoretical analysis, combining literature analysis and data analysis. Based on the analysis of renewable energy policies in countries with relatively mature energy transitions, it analyzes the status quo, implementation effect, and problems of renewable energy policy in China and proposes policy suggestions. According to the research, the existing problems are as follows: (1) diminishing marginal effect of policies, (2) policy adjustment is not timely and lacks details and operability, (3) coordination conflicts between the old and new policies, (4) unreasonable policy supply structure, and (5) the negative impact of subsidy policy is increasing. Therefore, this paper argues that China's renewable energy industry policy cannot effectively support the low-carbon energy transition. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to quantify the level of new-type urbanization and unravel the spatial and nonlinear effects of new-type urbanization and technological innovation on industrial carbon emissions. Although the impact of traditional urbanization levels on carbon emissions has been widely studied, there is still a huge room for optimization, and the impact of new-type urbanization on carbon emissions has not yet been clarified. Selecting 37 cities in the Yangtze River Delta as a research sample, this paper measures the new-type urbanization based on an evaluation system we build. Consequently, we assess the spatial and nonlinear effects of new-type urbanization and technological innovation on carbon emissions by the spatial Durbin model and non-parameter addictive model, respectively. The results indicate that the new-type urbanization and low-carbon city pilot policy have significant spatial spillover effects on reducing carbon dioxide emissions, while the economic growth plays a positive role in increasing carbon emission. As for nonlinear effects, there is a significant inverted "N"-shaped relationship between the level of new-type urbanization and carbon dioxide emissions, while the nexus between technological innovation and carbon emissions is an inverted "U"-shaped relationship. This paper provides a new perspective for confirming the mechanism of the new-type urbanization on carbon emissions. Meanwhile, these findings are of significance for the relevant authorities in China to develop appropriate policy in carbon dioxide emission reduction. [ABSTRACT FROM AUTHOR]

Global warming has endangered the natural ecosystem's balance, as well as human existence and development, and it is mostly caused by carbon dioxide. Identifying carbon emission characteristics and predicting carbon emission reasonably is helpful to provide indication for the effective design of emission reduction path. The most literature use a single prediction model; this paper predicts carbon emission using a number of strategies based on previous research. Considering the prediction accuracy, advantages, and disadvantages of each method, a new method combining autoregressive integrated moving average (ARIMA) model and NAR neural network (NAR-NN) is proposed; in addition, this paper attempts to explain the carbon emission characteristics and emission reduction paths of each region from the new perspective of clustering. First, the results show that China's carbon emission features can be divided into four categories: low-carbon demonstrative type, low-carbon potential type, high-carbon developed type, and high-carbon traditional type. Moreover, low-carbon demonstrative type includes merely Beijing and Shanghai, low-carbon potential type is distributed in the southeast coastal areas of China, the high-carbon developed type is mainly distributed in Northeast China, and the western region basically belongs to high-carbon traditional type. Second, ARIMA model and NAR-NN are the two best methods in terms of prediction effect, and the combined model has better prediction effect than the single model. Third, carbon emissions in most regions of China will increase in the next few years; the time of carbon peak in the east is earlier than that in the west regions of China. Beijing will probably be the first region in China to complete the carbon peak. Besides, there is a certain correlation between the carbon peak time and the type of carbon emission in each region. [ABSTRACT FROM AUTHOR]

In the context of the "peak carbon dioxide emissions" and "carbon neutrality" strategic goals, how green finance can prompt private enterprises to achieve green upgrading has become an important issue to be solved. This paper empirically examines the effect mechanism of green credit policy on private enterprises' green innovation by using the difference-in-differences model based on the manually collected green patent data and matching financial data of Chinese listed private enterprises from 2009 to 2019. It is found that the implementation of green credit policy has a significant negative impact on the quality of green innovation of heavy-polluting private firms relative to non-heavy-polluting private firms, and this conclusion is still valid after replacing the explanatory variables, expanding the sample range, changing the model setting, and excluding the interference of other policies during the sample period. The results of the mechanism suggest that green credit policy negatively affects the quality of green innovation of heavy-polluting private firms by limiting their access to financing for loans and the capital market. Further study finds that commercial banks can reduce their non-performing loan ratio and increase their revenue growth rate by extending green credit funds to improve their business performance. It provides insights for better implementation of green credit policy and promotion of green economy development. [ABSTRACT FROM AUTHOR]

Whether environmental regulation policy can achieve the double dividend of pollution control and employment promotion is a problem that warrants further discussion. This paper is a study of the effect of environmental regulation on the employment scale and employment structure. Based on matching data, the empirical results show that environmental regulations enhance the employment scale of enterprises. From the perspective of the employment structure, the labor redistribution caused by environmental regulation is reflected mainly in employment creation and employment destruction effects, which lead to the optimization of the employment structure. Further research shows that environmental regulations expand the employment scale but have different impacts on the employment structure in the developed and undeveloped regions of China. In addition, internal and external factors such as enterprise innovation and the institutional environment may affect the relationship between environmental regulation and the employment of enterprises. This paper provides theoretical support to promote the construction of an ecological civilization and the alleviation of employment pressure. [ABSTRACT FROM AUTHOR]

To cope with the coronavirus disease (COVID-19), national or sub-national regions have carried out many powerful anti-pandemic measures such as locking down, which may improve their regional air quality. This paper examines the relation between regional air pollution and work resumption from a novel post-pandemic perspective. Using a unique panel dataset on China's detailed industrial electricity consumption, this paper does not find a positive relation between post-COVID-19 work resumption and regional air pollution during China's early-stage recovery. This result is obtained after controlling for province and date fixed effects, as well as local weather conditions. However, the positive relations are found in a particular sub-sample of large industrial enterprises and a particular sub-sample of April. These findings indicate that large industrial enterprises may recover first, and the resumption is progressing gradually. Finally, several policy implications are provided, which are essentially helpful for other countries' post-pandemic recovery. [ABSTRACT FROM AUTHOR]

Continuously improving freshwater aquaculture efficiency will promote the sustainable development of freshwater aquaculture, which is crucial to ensure aquatic food supply. In particular, measuring the total factor productivity (TFP) of freshwater aquaculture to find ways to improve its efficiency is of great significance to sustainable development of freshwater aquaculture industry. Therefore, based on directional distance function, this paper constructs a meta-frontier Malmquist index (MMI) model by considering the regional heterogeneity to evaluate the TFP of freshwater aquaculture of China from 2004 to 2019. The results show that (1) from the perspective of time, TFP fluctuated significantly from 2004 to 2012, while after 2013, TFP remained around 1 with small fluctuation. In other words, freshwater aquaculture in China began to maintain a relatively negative state of development. (2) From a regional point of view, this study found that freshwater aquaculture TFP of inland region is better than the TFP of coastal region. (3) From the decomposition index, the variation of freshwater aquaculture TFP was driven by the combined effect of technology change (TC) and technical efficiency change (EC). In addition, the decomposition index efficiency shows that the technical efficiency decreases and the management efficiency changes little. (4) The gap of freshwater aquaculture technology in coastal areas is very small, and close to the optimal technical level. While in inland region, on the contrary, there is more room for improvement. According to the above empirical results, this paper finally gives some policy suggestions to improve the TFP to ensure the sustainable development of freshwater aquaculture. [ABSTRACT FROM AUTHOR]

Current studies do not provide a consensus on whether digital technology innovation can reduce enterprise carbon intensity despite the rise of the digital economy. This paper examines the role and influence pathway of digital technology innovation on enterprise carbon intensity using data from A-share listed enterprises in China's manufacturing industry from 2012 to 2021. The findings indicate that (1) digital technology innovation has been found to significantly reduce enterprise carbon intensity, as confirmed by numerous robustness and endogeneity tests. However, its inhibitory effect on carbon intensity shows a marginal decreasing trend. (2) In the heterogeneity analysis, it was found that digital technology innovation significantly reduces the carbon intensity of consuming coal, coke, kerosene, and diesel. From various perspectives, including enterprise, industry, and external environment, there are significant differences in the carbon reduction effects of digital technology innovation. (3) The analysis of impact paths reveals that digital technology innovation can affect enterprise carbon intensity through three paths: improving productivity, enhancing green innovation efficiency, and adjusting energy consumption. (4) Upon further analysis, it was discovered that the spillover effect of digital technology innovation is more pronounced in the industry cohort of enterprises. Additionally, digital technology innovation plays a positive role in enhancing enterprise ESG performance. The paper's findings offer empirical evidence and decision-making references for the government to develop reasonable policies for reducing carbon emissions, promoting green and low-carbon enterprise transformation, and actively and steadily achieving the goal of carbon peaking and carbon neutrality. [ABSTRACT FROM AUTHOR]

The impact of air pollution is one of the hotspots attracting continuous scholarly attention, but the comprehensive statistical and visual analysis reviews are few. Employing the method of bibliometric analysis, this paper took the relevant literature from 1996 to April 2022 on the Web of Science as the research object. Through the methods of keyword co-occurrence analysis and burst analysis, the spatiotemporal evolution trend, cooperation network, outstanding scholars, knowledge base, and research focus of air pollution impact research are visually presented. Via constructing a common word matrix of high-frequency words, clustering analysis is used to aggregate high-frequency keywords into 24 clusters. By the strategic coordinate analysis method, the relationships within and between clusters were revealed. The main findings include (1) research on the impact of air pollution mainly focusing on human health; (2) the six keywords with the highest centrality are California, hydrocarbons, dioxide, generation, Asia, and diesel; (3) these 11 clusters may be developed into future research hotspots: particulate matter, nitrogen oxides, mortality, ozone, pollution, air quality, asthma, children, epidemiology, aerosols, and polycyclic aromatic hydrocarbons; and (4) seven topics are research hot: daily mortality, long-term exposure, coronary heart disease, concentration, North China plain, traffic-related air pollution, and air pollution. [ABSTRACT FROM AUTHOR]

In the context of increasing global resource and environmental problems, it is of great practical significance to accurately test the impact of various factors on energy use efficiency for maintaining national energy security and formulating relevant policies. This paper measures firms' total factor energy efficiency (TFEE) using the two-stage stochastic frontier method within the data envelopment analysis (DEA) framework, leveraging data from listed firms in China spanning 2010 to 2022. Employing the establishment of free trade zones (FTZs) as a quasi-natural experiment, we apply the staggered differences-in-differences (DID) and stacked DID methods and analyze the impact of FTZs on firms' TFEE. The results show that the establishment of FTZs significantly promotes the improvement of firms' TFEE, and it has a greater promotion effect on heavily polluting, non-manufacturing, state-owned, private, and small-scale firms. The results of the mechanistic analysis showed that the promotion effect of FTZs on firms' TFEE is mainly realized through three channels: increasing government subsidies, reducing the financing constraint effect, and encouraging the technology innovation effect. Furthermore, industry-level decomposition results indicate that the surge in industry energy efficiency primarily results from improvements within firms rather than inter-industry variations. This paper's results propose that countries can enhance energy efficiency by progressively endorsing the implementation of FTZs. [ABSTRACT FROM AUTHOR]

Since 2005, China's outward foreign direct investment (OFDI) has increased year by year, which corresponds to the continuous decline of energy intensity. But there is limited literature concerning their relationship nowadays. To answer whether or not OFDI can reduce energy intensity, this paper selects data from 29 provinces in China from 2006 to 2015 and establishes a fixed-effects model to analyze the relationship. Further, this paper divides OFDI into technology-intensive ones and non-technology-intensive ones in order to distinguish the impact of outward foreign direct investment from different types of enterprises on the energy intensity. Combined with the micro-data of A-share listed companies in Shanghai and Shenzhen stock exchanges, we find that OFDI plays a significant role in reducing the energy intensity in China, and OFDI of high-technology-intensive enterprises has a greater effect on the decrease of energy intensity than that of low-technology-intensive enterprises. This paper classifies OFDI from the perspective of enterprise technology intensity, which enriches the existing research results in the field of international cooperation and energy intensity. It also overcomes the limitations of previous literature data and provides new evidence for encouraging high-tech enterprises to strengthen international cooperation from a micro level. [ABSTRACT FROM AUTHOR]

Improving energy efficiency is an important measure of environmental governance. At present, studies on the impact of high-speed rail on energy efficiency need to be further studied. This paper constructs panel data of 285 cities at prefecture-level and above in China from 2003 to 2017, and uses the difference-in-difference (DID) to study the impact of high-speed railway on urban energy efficiency. Based on the theories of "factor flow," "knowledge spillover," and "center-periphery," this paper discusses the influence mechanism and heterogeneity of high-speed railway on energy efficiency. The empirical results show that high-speed railway can significantly improve energy efficiency, and the conclusion is still valid after parallel trend test, propensity score matching and difference-in-difference (PSM-DID) test, and instrumental variable method. The results remained true after a series of robustness tests. Mechanism analysis shows that high-speed railway can improve energy efficiency by promoting industrial structure upgrading, technological innovation, and market integration. Analysis of heterogeneity shows that the promotion effect of high-speed railway on energy efficiency is greater in central and western cities and core cities. This study provides useful enlightenment for optimizing China's high-speed rail construction planning and seizing the opportunity of high-speed rail development to improve energy efficiency. [ABSTRACT FROM AUTHOR]

This paper studies the relationship between the coal-to-gas program and air pollution in China and provides micro-evidence of the mechanism from the perspective of households. Using daily air pollution and meteorological data between January 1, 2016, and January 1, 2020, we assessed the effect of the coal-to-gas program on air pollution by introducing the regression discontinuity designs in time (RDiT). We found that the coal-to-gas program significantly improved air quality and brought significant economic benefits. In the short term, the coal-to-gas program can lead to more than 10 units of reduction in SO2, PM2.5, and AQI in the treatment group, while it can lead to more than 50 units in the long term. Using the difference-in-differences approach, we found that the coal-to-gas program has significantly reduced air pollution. Combined with the micro-panel data of the China Health and Retirement Longitudinal Study from 2011 to 2018, we found that the coal-to-gas program changes the household heating energy choices and that the probability of coal-fired heating of households in pilot areas is decreasing. The study suggests that non-clean energy in households should be further replaced to continue improving air quality. [ABSTRACT FROM AUTHOR]

Both "dual cycle" and "carbon neutral" policies have been implemented as national strategies in China. But will "dual cycle" policy help carbon neutral policy and how do "dual cycle" policy affect carbon neutral policy? This paper investigates whether unbalanced bidirectional foreign direct investment (FDI) hinders electricity efficiency. To do so, it uses the super slack-based version of the global Malmquist–Luenberger index to measure electricity efficiency in 30 provinces from 2001 to 2020. This paper uses panel threshold regression model, finds out that bidirectional FDI below 1.7174 will positively impact electricity efficiency, but the positive effects disappear when bidirectional FDI exceeds 1.7174. Thus, balanced bidirectional FDI in province is required to enhance electricity efficiency. [ABSTRACT FROM AUTHOR]

To achieve China's "double carbon" goal, it is necessary to make quantitative evaluation of the power grid enterprises' contribution to carbon emission reduction. This paper analyzes the contribution of power grid enterprises to carbon emission reduction from three points: power generation side, power grid side, and user side. Then, PLS-VIP method is used to screen the key influencing factors of carbon emission reduction contribution of power grid enterprises from three aspects: consumption of clean energy emission reduction, reduction of line loss emission reduction, and substitution of electric energy. Based on GA-ELM combined machine learning algorithm, we establish an intelligent evaluation model of power grid enterprises' carbon emission reduction contribution. Furthermore, according to the distribution law of key influencing factors, this paper uses Monte Carlo simulation method to calculate the contribution of power grid enterprises to carbon emission reduction by scenario, so as to evaluate the contribution of power grid enterprises to carbon emission reduction. Finally, combined with the relevant data of power grid enterprises from 2003 to 2019, this paper makes an empirical study on the completion of carbon emission reduction contribution and the promotion path. [ABSTRACT FROM AUTHOR]

As an emerging driving factor, the positive impact of renewable energy technology innovation (RETI) on inclusive low-carbon development (ILCD) may be undervalued or even neglected. This paper develops an evaluation system to measure China's ILCD by using provincial panel data from 2006 to 2020. Based on the combined perspective of spatial spillover effect and threshold effect, this paper examines the spatial spillover effects and the regional boundary of RETI on ILCD in different periods and further analyzes five heterogeneities. The results show that (1) RETI and ILCD are increasing steadily, presenting a spatial pattern of "high in the east and low in the west." (2) Overall, RETI significantly promotes ILCD in local and neighboring areas. RETI in the growth period inhibits local ILCD, which in the mature period promotes local and neighboring ILCD. (3) The spatial spillover boundary of the whole RETI is 1400 km, that of RETI in the growth period is 1000 km, and that of RETI in the mature period is 1600 km. (4) The promotion effect of RETI on ILCD enhances over time and shows a spatial pattern of "eastern > central > south > north > western." It is further found that RETI strongly promotes ILCD in non-resource-based, high marketization, and strong environmental regulation areas. Therefore, it is necessary to break down administrative and market barriers, strengthen inter-regional cooperation and interconnection of resource elements, and establish a dynamic management mechanism of "one province, one policy" according to the regional heterogeneity for providing decision-making reference in promoting global energy transition and climate governance. [ABSTRACT FROM AUTHOR]

Our world needs to develop clean energy to reach the target of carbon peak and carbon neutralization. As one of clean energy, wind energy should contribute to energy conservation and emission reduction. Wind power generation is an important field of wind energy application. However, the fluctuation and intermittency of wind can affect the safety of power system. Therefore, prediction of wind power accurately for wind power safety, dispatching, and power grid development is significant. This paper proposes a prediction model of wind power, and predicts the wind power of two wind farms. For the complex wind speed series, the variational modal decomposition (VMD) method is used to reduce its volatility before prediction. And this paper presents an improved method to improve the prediction efficiency when least square support vector machine (LSSVM) predicts stationary series. The prediction result shows that the proposed model improves the prediction of wind power effectively, provides an effective method for wind farm to predict the wind power, and makes contributions to reducing carbon emissions and environmental protection. [ABSTRACT FROM AUTHOR]

With the rapid growth rate of China's economy, the extensive pattern of economic growth of "high energy consumption and low output" has magnified the constraints of energy issues on China's economic development and environmental protection, which highlights the importance of improving energy efficiency. As one of the three major economic zones in China, the Pearl River Delta region also faces high energy consumption and pollution emissions while developing at a high speed. Hence, improving the energy efficiency of the Pearl River Delta region is needed, as it not only is conducive to driving its development of the surrounding green economy, but also promotes the subsequent sustainable economic development. However, there are few literatures on the calculation and analysis of energy efficiency in the Pearl River Delta, and lacking a systematic analysis of input–output index system of energy efficiency measurement. Therefore, this paper calculates the energy efficiencies and the Malmquist indexes based on the panel data of the nine cities in the Pearl River Delta from 2005 to 2019 through super-efficiency SBM model and Malmquist index method by using MAXDEA and MATLAB software. The result illustrates that all regions in the Pearl River Delta except Guangzhou and Shenzhen show obvious energy inefficiency, which is mainly caused by the imbalance between technical efficiency and scale efficiency. Based on the calculation results, this paper gives some relevant suggestions for the further approach of energy reform in the Pearl River Delta according to the calculation results. [ABSTRACT FROM AUTHOR]

To cope with climate change, China commits that it will strive to achieve carbon peaking by 2030. Using the Cointegration model and the Markov Chain model, this paper forecasts China's carbon emissions during 2019–2030 in six scenarios, and assesses the contribution of optimizing the energy mix to China's carbon peaking. The research obtains three main conclusions. Firstly, optimizing the energy mix will contribute to achieving China's carbon peaking. In the economic slow-growth scenario, taking China's planned target of energy mix (PTEM) into account, the carbon peaking year will be brought forward from 2028 to 2023. In the economic medium-speed-growth scenario, optimizing the energy mix will make China achieve carbon peaking in 2028. Without considering the PTEM, however, the carbon emissions will not peak before 2030. In the economic fast-growth scenario, the peaking year will not occur whether considering the PTEM or not, but the growth rate of carbon emissions with the PTEM will be far lower than that without considering the PTEM. Secondly, in all three economic growth scenarios, optimizing the energy mix will largely reduce the growth rate of carbon emissions, and thus significantly reduce the peak value of carbon emissions. Thirdly, optimizing the energy mix has a negative adjusting effect on the impact of economic growth on the growth rate of carbon emissions, and the negative effect rise as the economic growth rate increases. [ABSTRACT FROM AUTHOR]

In-depth research on the spatiotemporal patterns and evolution trend of urban land use carbon emission intensity (ULUCEI) can reveal the internal relationship between urban land use and carbon emissions, which is crucial for achieving carbon emission reduction and "double carbon" targets. This paper proposed a conceptual framework of ULUCEI; the methods of kernel density estimation (KDE), exploratory spatial data analysis (ESDA), and spatial Markov chains were adopted for exploring the spatiotemporal patterns and evolution trend of China's ULUCEI from 2000 to 2017. The following conclusions are drawn through research. (1) There was an increasing trend in ULUCEI in China from 0.102 in 2000 to 0.283 in 2017. From the regional perspective, the ULUCEI in the eastern region is markedly higher than that in the central and western regions. Moreover, the results of nuclear density estimation indicate that China's ULUCEI shows an obvious upward and polarized trend. (2) China's ULUCEI shows a positive spatial autocorrelation. The types of spatial agglomeration include "high-high" agglomeration, "high-low" polarization, "low-high" collapse, and "low-low" homogeneity, and there are obvious disparities in the distribution rules of cities with different spatial agglomeration forms. (3) China's ULUCEI presents strong stability and "club convergence" trend. Moreover, spatial factors significantly affect the dynamic transition of China's ULUCEI, and its effect on the shifting upwards gradually enhances with increasing lag type. This paper therefore suggests that policymakers should formulate differentiated urban land low-carbon use models and carbon emission reduction policies to reduce ULUCEI. [ABSTRACT FROM AUTHOR]

This paper uses bibliometrics to characterize the knowledge systems of big data, artificial intelligence (AI), and energy based on the Science Citation Index Extension (SCI-E) and Social Science Citation Index (SSCI) of the Web of Science from 2001 to 2020. Results show that China is the country with the highest number of publications (1115), accounting for 29% of the total; however, the most influential country in the field is the USA, with an h-index of 75. The Chinese Academy of Sciences publishes the largest number of papers (104) and plays a vital role in the collaboration network. The study also reveals that the IEEE Access is the most productive journal (195) in terms of the number of publications, and engineering is the most popular discipline (1526). The key theoretical foundation includes deep learning (293), big data (105), energy consumption (79), and reinforcement learning (40). The application of big data and AI in the field of energy focuses on smart grid, energy consumption, and renewable energy. Early research frontiers involve optimization and prediction of energy-related problems using the genetic algorithm and neural networks. Since 2013, energy big data have gained prominence. At present, machine learning, deep learning, and fog computing are frequently combined with energy saving. In the future, big data and AI will be utilized to promote the application of renewable energy and energy-saving renovation of buildings. These findings can help researchers understand the developmental trends and correctly grasp the research direction and method of the emerging interdisciplinary field. [ABSTRACT FROM AUTHOR]

In China, exploring the relationship between human capital and green economy in the context of economic transformation can promote the construction of an ecological civilization and high-quality economic development. This paper is dedicated to assessing the impact of human capital stock, human capital structure, and the difference between the two on China's green economy. Using the super-efficiency slack-based measure (SBM) model, this paper evaluated the green total factor productivity (GTFP) of 30 Chinese provinces to assess the greenness of its economy and analyzed its spatiotemporal evolution from 2000 to 2017. A spatial error model (SEM) was established to explore the impact of human capital on green economy. The results show that (1) the GTFP of China increased continuously from 0.219 to 0.457, showing a regional spatial differentiation of "eastern region > central region > western region." The spatial gaps of the green economy in the east-west and north-south directions are narrowing. (2) Moran's I index and Moran's I scatter plot indicate a significant spatial correlation between human capital and China's green economy. The local spatial correlation between human capital and green economy is mainly characterized by "high-high" and "low-low" types of agglomeration. (3) The effects of human capital stock and human capital structure on green economy were both positive, with coefficients of 0.0005 and 0.1601, respectively, but the effects of human capital structure were not significant. (4) The results of regional regression show that the difference between the human capital impact coefficients on green economy in the eastern and midwestern regions is small. The impact of human capital stock and human capital structure on green economy is consistent with the national level results. It can be preliminarily concluded that the development of China's green economy relied more on improving the human capital stock than on the improvement of the human capital structure. This study further enriches the literature on the green economy and provides information that can support government policy-making. [ABSTRACT FROM AUTHOR]

As a Chinese solution to build a community of human destiny, Belt and Road Initiative (BRI) has shown China's international responsibility by promoting its green development. Based on the annual panel data of Chinese cities from 2004 to 2018, this paper systematically explores the effect of BRI on the Green Total Factor Productivity (GTFP) of cities along its domestic route using the difference-in-differences (DID) method. The results of the study show that (1) BRI significantly increases the GTFP of cities along its domestic route, and this finding holds after excluding a series of robustness tests such as endogeneity issues and other policy disturbances. (2) BRI promotes the growth of GTFP in the region mainly through improving science and technology innovation, increasing foreign direct investment and enhancing trade cooperation. (3) From the perspective of heterogeneity, the promotion effect of BRI on the GTFP of inland cities along the route is much higher than that of coastal cities, and cities along the route with stronger environmental concerns have a more significant enhancement effect. (4) Based on the policy context and the undertaking of role functions, there is a significant positive linkage effect between BRI Initiative and the Free Trade Zone (FTZ) construction in promoting GTFP growth. (5) From a spatial perspective, BRI has not only increased the GTFP of cities along the route, but also radiated the growth of GTFP in neighboring cities along the route. The conclusion of this paper provides a policy reference and theoretical basis for further building the green "Belt and Road" and promoting the sustainable development of China's economy and high-quality transformation. [ABSTRACT FROM AUTHOR]

Under the background of China's ecological civilization construction, enterprises green technology innovation (GTI) has attracted more and more attention. In this paper, the internal factors and external factors, subjective factors, and objective factors of each relevant subject are comprehensively considered, and the analysis framework of the impact mechanism of enterprise GTI is constructed. Then, taking 211 heavily polluting listed enterprises in China from 2010 to 2019 as the sample, integrating the mediating effect model and the moderating effect model, this paper empirically discusses the relationships among corporate endowments, executive characteristics, and enterprise GTI. The results demonstrate that corporate endowments have a positive impact on GTI, and executive characteristics act on GTI as a mediating variable during the impact process; market forces respectively play a weakening and strengthening role in moderating the main effect and the intermediate effect; government intervention and social background have positive moderating effects on the relationship between executive characteristics and GTI; the three moderating variables have a remarkable joint-moderating effect on the relationships between executive characteristics and GTI. [ABSTRACT FROM AUTHOR]

Green innovation (GI) has the dual attributes of green development and being innovation driven, and it has become an inevitable choice for solving the prisoner's dilemma of environmental protection and economic development under the action of the concept of sustainable development in the new era. This paper aims to clarify how environmental regulation (ER) can achieve a win‒win situation of GI and environmental protection by using data from prefecture-level cities in China and creating a dynamic panel model, quantile model, spatial econometric model, and panel threshold model to empirically analyze the dynamic effect and spatial effect of ER on GI as well as the nonlinear characteristics of the relationship between them and to examine the moderating effect of foreign direct investment (FDI). The results show that ER significantly promotes the development of the GI level and that FDI can play a positive moderating role. The impact has regional heterogeneity, time period heterogeneity, and resource endowment heterogeneity. After several robustness tests, the empirical conclusions are still credible. Based on the empirical conclusions, this paper makes policy suggestions on ER, foreign investment introduction, and the coordinated development of regional GI. [ABSTRACT FROM AUTHOR]

China needs to achieve its carbon peaking target with minimal economic costs. This paper proposes a framework for achieving the carbon peaking target that emphasizes economic effects. Based on the prediction, the parametric directional distance function (DDF) is adopted to calculate the total factor carbon emission efficiency and marginal carbon abatement cost in each region of China before 2030, and the allocation scheme of the abatement tasks necessary for carbon peaking is optimized from the perspective of least cost. The empirical results show the following: (1) The predicted rapid growth of China's economy from 2020 to 2030 will lead to a rapid increase in marginal abatement costs, with the average marginal carbon abatement cost increasing from 8,833 yuan/ton to 15,077 yuan/ton. The cost of carbon emission reduction in the future is very expensive. (2) The measured marginal abatement costs in China are positively correlated with carbon emission efficiency. In order to ensure economic development, developed regions should try to maintain the development trend, while the central and western regions take on more emission reduction tasks. (3) The emission efficiency is improved by optimizing the allocation scheme of the abatement tasks required to reach the peak, and the scientific and orderly path to reach the peak of each province and the corresponding lowest economic cost are obtained. This paper are of great theoretical and practical significance for the initial quota allocation in carbon trading market and ensuring the achievement of carbon peaking target under economic effect. [ABSTRACT FROM AUTHOR]

Rapid development and agglomeration of manufacturing industries in China inevitably lead to serious environmental pollution problems. The government restrains development of manufacturing industries through environmental regulation policies, but this may affect manufacturing industries agglomeration. Therefore, studying the impact of environmental regulation (ER) on manufacturing agglomeration (MA) is a critical prerequisite for the sustainability of China's manufacturing industry. Based on the panel data of 41 cities in Yangtze River Delta (YRD) region of China from 2003 to 2017, this paper explores the threshold effect of ER on MA using a panel threshold model and analyzes the heterogeneity impact of ER on MA in different regions and analyzes the dynamic mechanism and contribution of each influencing factor on MA using a panel vector autoregressive model. The results show that (1) there is a double threshold effect of ER on MA, showing an inverted "U"-shaped effect of rising and then falling; there are threshold effects of ER on MA based on foreign direct investment (FDI) and economic development level (EDL). The effect of ER on MA has the threshold effect under different FDI and EDL level, in which the effect based on FDI shows an inverted "U" shape relationship of rising and then falling; the effect based on EDL shows a growing trend. (2) There are 29 cities in YRD region in the "weak regulation" or "strong regulation" stage, both of which are not conducive to MA. (3) ER has a facilitating effect on MA, but with the extension of forecast period, this facilitating effect turns into an inhibiting effect. MA is mainly influenced by itself and transportation conditions (TC). Our study can provide some insights for improving the ecological environment and promoting the development of manufacturing clusters in YRD region. [ABSTRACT FROM AUTHOR]

The complex interaction between emissions, meteorology, and atmospheric chemistry makes accurate predictions of particulate pollution difficult. Advanced data mining techniques can reveal potential laws, providing new possibilities for understanding the evolution and causes of air pollution. Based on the Granger method and block modeling analysis, this paper explored the intercity spillover effects of hourly PM2.5 in Hubei Province, China, to determine the specific role (i.e., overflow, limited overflow, bilateral, inflow, and limited inflow) of each city on regional pollution formation. Furthermore, a dynamic Apriori algorithm considering time-lag effects was used to mine the spatio-temporal associations of extreme PM2.5 pollution events among different cities. Results suggest that the northern and central cities with high-level PM2.5 concentration in Hubei have a significant spillover effect, whereas the eastern and southern cities generally play a role as the sink of pollutants. Based on the association rules of extreme PM2.5 pollution, four main pollutant transport channels were excavated and well matched with the trajectories extracted by the atmospheric model. This paper provides new insights for exploring the interaction of intercity particulate pollution, which is a supplement and cross-validation of the model results. [ABSTRACT FROM AUTHOR]

The world is facing the problem of resource scarcity and environmental degradation. Improving energy efficiency is an effective way to reduce energy consumption and reduce pollutant emissions. Based on relevant data from 30 Chinese provinces from 2011 to 2019, this paper constructs energy efficiency indicators by establishing a super-efficient three-stage SBM-DEA model. It explores the impact of digital finance on energy efficiency using a systematic generalized moment estimation method and constructs an analytical framework for the impact of digital inclusive finance on energy efficiency from the breadth of coverage, depth of use, and degree of digitization of digital inclusive finance. In addition, this paper examines the differences in the impact of digital inclusive finance on energy efficiency from a sub-regional perspective. Research indicates the following: (1) At the national level, the relationship between digital inclusive finance development and energy efficiency in China shows an inverted "U"-shape; the breadth of digital financial coverage, the use of digital insurance services and digital credit services, and the degree of digitalization of digital finance all have significant effects on energy efficiency. (2) From a regional perspective, the impact of digital inclusive finance on energy efficiency has regional heterogeneity. Based on this finding, first, the government should speed up the construction of digital financial infrastructure to promote the further development of digital finance. Second, the government should take appropriate measures to regulate industry giants. Third, the government should adjust measures to local conditions when formulating policies. The above research has certain implications for improving the targeting of digital finance–related policies and promoting the high-quality development of China's economy. [ABSTRACT FROM AUTHOR]

Pastoral areas are the key difficulty in China's pursuit of common prosperity and a key region for China to build the northern ecological safety barrier and to realize the Two Centenary Goals. It is of great significance to scientifically evaluate the quality of rural life (QRL), measure the relative poverty level (RPL), and identify the relatively poor areas, making it possible to dock poverty elimination with rural revitalization. Based on the socio-economic data of 18 pastoral areas in Inner Mongolia, this paper draws on spatial layout theory to evaluate QRL and measures RPL by the natural breakpoint method and then identifies the relatively poor areas in Inner Mongolia. The results show that (1) the QRLs of pastoral areas in Inner Mongolia were unbalanced and highly polarized. The mean score of QRLs was 0.2598. Eleven (61.11%) of the counties/banners had a QRL smaller than the mean score. On the spatial layout of QRLs, the western areas were stronger than the central areas. High QRL counties/banners are mainly concentrated in the western region. In the central region, the QRLs were very fragmented, falling onto all five levels. (2) The pastoral areas in Inner Mongolia differed significantly in RPL. The mean score of RPL stood at 0.3788. Nine counties/banners (50%) had an RPL greater than the mean. Contrary to the spatial layout features of QRLs, the central pastoral areas in Inner Mongolia had stronger RPLs than the eastern ones. High RPL counties/banners are mostly clustered in the central region. The spatial layout of RPLs is relatively reasonable in the central region: the RPLs decreased gradually from Dorbod Banner. (3) Nearly 45% of the pastoral areas in central and western Inner Mongolia face serious relative poverty and a high risk of returning to poverty. Eight counties/banners (45%) were identified as high composite relative poverty areas. From spatial layout, the composite relatively poor counties/banners clustered clearly, mainly in the western region. Finally, this paper establishes a warning mechanism against large-scale returning to poverty, aiming to lower composite RPL. The research results provide empirical reference and implementation path for consolidating the results of poverty eradication and facilitating rural revitalization. [ABSTRACT FROM AUTHOR]

At present, China's economy is transforming from rapid development to high-quality development, and environmental pollution stands out as an urgent need to be addressed. Fiscal decentralization is considered to confer economic incentives on local governments to obtain the right to gain and spend in economic growth. However, at the same time, political incentives are given to local officials under the promotion mechanism based on gross domestic product (GDP) assessment, and these two incentives become key to the environmental performance of the jurisdictions. Therefore, this paper incorporates fiscal decentralization, promotion incentives, and environmental pollution into a unified framework and theoretically analyzes the effects of fiscal decentralization, promotion incentives on environmental pollution, and the intrinsic mechanism of action. Using panel data of 30 Chinese provinces from 2002 to 2018, we examine that fiscal decentralization significantly promotes environmental pollution, and this performance is more obvious in economically underdeveloped regions. In terms of its mechanism of action, fiscal decentralization affects environmental pollution by increasing the demand for foreign direct investment, inhibiting technological progress, and enhancing environmental regulation, while foreign direct investment and technological progress significantly inhibit environmental pollution, but environmental regulation does not present a role of pollution control. Further study finds that under the consideration of "GDP-based promotion incentives," local officials will generate "competition for investment," relax environmental standards for FDI, and generate "competition for growth", which will inhibit technological progress and incomplete enforcement of environmental regulations, thus exacerbating local environmental pollution. On this basis, this paper proposes to further deepen the fiscal system reform, promote the optimization of local government competition system, and effectively restrain the vicious competition behavior of local officials under the fiscal decentralization system, so as to provide relevant insights for realizing China's economic transformation as well as high-quality economic development. [ABSTRACT FROM AUTHOR]

Management of economic growth targets is a universal measure employed by worldwide governments for macroeconomic regulation. This paper aims to empirically investigate the impact of economic growth targets set by governments of prefecture-level cities on the environmental regulation intensity. We extracted panel data on annual economic growth targets and environmental regulation indicators from the government work reports (2009–2016) of 284 China's prefecture-level cities. The study concludes that an increase in economic growth target significantly weakens the intensity of environmental regulation. The conclusion still holds true after robustness tests, including changing measurement variables, regression samples, and conducting endogenous tests. The underlying reason for the inhibitory effect may be that in order to achieve economic growth targets, local governments prefer less stringent environmental regulations. They subsequently expand outputs in the short term by increasing the proportion of secondary industry in GDP, land transfer area, and fixed asset investment. Further research in this paper also finds that only cities with low economic development levels and low openness to the outside world experience the negative effect of a local government's annual economic growth target on environmental regulation intensity. [ABSTRACT FROM AUTHOR]

Carbon emissions from animal agriculture are a major source of global greenhouse gases. This paper measures the spatial and temporal characteristics and evolution patterns of carbon emissions from livestock farming in China and 31 provinces from 2001 to 2020 based on IPCC coefficients. The paper also uses Moran's I index, kernel density estimation, and spatial Markov chains for the analysis. The results show that the total carbon emissions from China's livestock sector show a fluctuating downward trend. And livestock carbon emissions are concentrated in areas with better resource endowments, with grassland and grain-producing areas dominating China's livestock carbon emissions. The spatial analysis shows that the spatial correlation of the national livestock carbon emissions is increasing, showing prominent local aggregation characteristics, mainly in the form of high-high and low-low aggregation. The transfer of carbon emissions from China's livestock industry shows strong spatial and temporal dependence, and the transfer of regional carbon emissions is limited by the original type and stock of carbon emissions, showing growth inertia and path dependence. The findings of this paper can provide suggestions for planning and modifying policies to reduce carbon emissions in China's livestock industry. [ABSTRACT FROM AUTHOR]

Based on the system theory and Pareto efficiency theory, this paper, based on the data of listed companies in China's A-share manufacturing industry in 2011–2022, explores the impact of market-driven green finance and government-guided green finance on the carbon emission intensity of manufacturing enterprises, and analyzes the intermediary role of debt financing cost. A negative "U" relationship exists in market-driven green finance/government-guided green finance and the carbon emission intensity of manufacturing enterprises. Further research shows that under the higher debt financing cost, market-driven green finance played a weaker carbon reduction effect. The heterogeneity analysis found that market-driven green finance can have a significant non-linear impact of "promoting growth first and weakening later" on the carbon emissions of energy-saving and environmental protection enterprises, large enterprises, and enterprises with high human capital levels. Government-guided green finance has a significant non-linear impact on non-energy-saving and environmental protection enterprises and small enterprises. This paper provides the theoretical basis and practical inspiration for the government to formulate relevant low-carbon development policies and promote the innovation of green financial tools in the financial market. [ABSTRACT FROM AUTHOR]

Carbon emissions from the electricity industry (CEEI) account for a large proportion of China's total carbon emissions, and it is important to study the spatial correlation between CEEI and the influencing factors to promote cross-regional synergistic emission reduction and low-carbon development of the power system. In this paper, the quasi-input-output (QIO) model is applied to assess the transfer of carbon emissions generated by electricity trading based on the consideration of electricity carbon transfer, and the exploratory spatial data analysis (ESDA) method is applied to analyze the spatial correlation effect of carbon emissions from China's electric power sector from 2001 to 2020, analyzes its distribution pattern in both spatial and temporal dimensions, and applies the improved logarithmic mean Divisia index (LMDI) two-stage decomposition model to decompose the changes in CEEI into 11 influencing factors from the perspective of the whole industrial chain of power production, transmission, trade, and consumption. The research results show that (1) the spatial distribution of CEEI has obvious unevenness and aggregation characteristics, with high-high aggregation areas and hot spot aggregation areas generally concentrated in the North China Power Grid and the East China Power Grid, but the aggregation trend is gradually decreasing, while low-low aggregation areas and cold spot aggregation areas are concentrated in the Northwest China Power Grid and the Central China Power Grid, but the area is very limited. (2) The direction of carbon emission diffusion in China's electricity industry is gradually transitioning from southwest-northeast to northwest-southeast, and the east-west diffusion trend is stronger than the north-south diffusion trend and carbon emissions are gradually shifting to the northwest grid. (3) The total amount of electricity production is the most influential factor in the change of CEEI, driving the cumulative growth of CEEI by 4495.34 Mt, followed by GDP per capita and electricity consumption intensity. Coal consumption for power generation, the share of thermal power, and net electricity exports were the main factors inhibiting the increase in carbon emissions from the power sector, with cumulative contributions of −797.74 Mt, −619.99 Mt, and −47.76 Mt, respectively. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Carbon emissions have risen in line with China's economic expansion. The key to sustainable development is finding a way to strike a balance between economic expansion and environmental protection, so improving carbon emission efficiency is vital. This paper uses provincial data from 2010 to 2020 to account for total carbon emissions using the emission factor method and obtains carbon emission efficiency data on this basis. A dynamic spatial Durbin model is then used to empirically test the possible influencing factors. The results show that, firstly, the growth rate of total carbon emissions is generally in line with the growth rate of GDP, indicating that there is no 'decoupling' in the economic system. Second, regional carbon emissions and carbon emission efficiency are not necessarily related. Thirdly, there is a clear spatial effect on carbon emission efficiency. The eastern region has the highest carbon emission efficiency, the western region has the lowest, and the northeastern and central regions have little difference in carbon emission efficiency. Further spatial and temporal migration analysis reveals that five provinces have made the migration between 2010 and 2020. Fourthly, in the short term, the direct and indirect effects of the factors affecting carbon emission efficiency are insignificant, but in the long term, most of the factors have significant direct and indirect effects on carbon emission efficiency. Finally, based on the above research findings, this paper makes policy recommendations. [ABSTRACT FROM AUTHOR]

As digital economy flourishes, there have been fundamental changes in the patterns of economic development, social structure, and ecological environment, which are the key elements of inclusive green growth (IGG). However, whether digital economy can effectively contribute to IGG requires further investigation. This paper evaluates the direct and spatial spillover effect of digital economy on IGG of 280 cities in China during 2011–2019 using Spatial Durbin Model (SDM). It further explores how government environmental regulation (GER) moderates this facilitating effect. The empirical results show that digital economy significantly reinforces IGG while GER weakens the benefits of digital economy to IGG. There is a significant spatial spillover effect of digital economy on IGG in neighboring regions; specifically, IGG in peripheral cities is more significantly encouraged by digital economy than in central cities. In addition, digital development demonstrates the most significant impact on IGG in central regions of China, followed by the eastern regions, with western regions lagging behind. This paper contributes theoretically and empirically to promote digital economy selectively for IGG in different regions and provides a guideline for policymakers to achieve IGG through proper GER. [ABSTRACT FROM AUTHOR]

Agricultural carbon emission reduction is an important issue in environmental protection and development in China and the world. The farmland spatial transition is an important path for agricultural modernization in developing countries such as China. How can farmland spatial transition promote agricultural carbon emission reduction? This paper aims to explore the mechanisms and spatial-temporal effects of farmland spatial transition on agricultural carbon emission density. To study the mechanisms and effects, we establish the random effect model, the threshold model, and the GTWR model with 2018 counties in China from 2000 to 2020. The research shows the farmland spatial transition mainly promotes agricultural carbon emission reduction through the interaction mechanism of large-scale production and specialized production, intermediary, and threshold mechanisms of agricultural technology. The result also shows that specialized farmland management is the main driving force of agricultural carbon emission reduction for farmland spatial transition. Moreover, the impact of farmland spatial transition on agricultural carbon emission reduction has significant spatial and temporal differences. The most significant regions are located in the middle and lower reaches of the Yangtze River plain, while the least are the north and southwest. Besides, the impact of the farmland spatial transition on agricultural carbon emissions reduction has a "V" shape over time, indicating China's agricultural carbon emission reduction is facing enormous economic and social development challenges. Our research reveals the various mechanisms and spatial-temporal effects of the transition of farmland spatial morphology on agricultural carbon emission with an evaluation framework, which is crucial to low-carbon agriculture with proper farmland use. [ABSTRACT FROM AUTHOR]

At present, the life and production of our society are still accompanied by high pollution emissions. The proposal of the "double carbon" goal puts forward clearer requirements for China's energy conservation and emission reduction process. To cope with stricter green development requirements, green finance came into being, contributing a new path to the realization of the "double carbon" goal. This paper is based on the panel data of 30 provinces and cities in China (except Tibet, Hong Kong, Macao, and Taiwan) from 2011 to 2020, using the fixed effect model, threshold model, mediator model, and SDM model to study the impact of green finance on carbon neutralization capacity and its impact path based on reasonable measurement of regional green finance development level and carbon neutralization capacity. The study found that due to the existence of the "green paradox" and "forced emission reduction", China's green finance has a significant positive U-shaped impact path on carbon neutralization capacity; at the same time, informal regulation has a significant single-threshold effect in this path. When informal regulation crosses 0.47, the impact of green finance on carbon neutralization capacity will change from negative to positive, overcoming the impact of the "green paradox"; there is a nonlinear mediating effect of marketization level and technological innovation in the path of green finance affecting carbon neutralization capacity. In addition, green finance not only affects local carbon neutralization capacity but also has a positive spillover effect on neighboring regions. [ABSTRACT FROM AUTHOR]