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Under the new development model, the digital economy has become a new engine to promote the green development of the economy and realize the goal of "double carbon". Based on the panel data of 30 provinces in China from 2010 to 2020, this paper empirically investigates the impact of the development of the digital economy on energy and carbon emissions using a series of econometric models such as baseline regression, a mechanism test, and the spatial Durbin model, etc. Common prosperity plays an intermediary role between digital economy development and carbon emissions; digital economic development optimizes resource allocation, effectively solves the problem of uneven resource distribution, and reduces energy and carbon emissions while achieving common prosperity. In addition, green innovation, industrial structure, urbanization level, R&D intensity, and the degree of marketization also have different degrees of influence on energy and carbon emissions. Therefore, the government should accelerate the construction of new digital infrastructure and implement the digital economy development strategy according to local conditions, so as to promote the digital economy to produce a more significant carbon emission reduction effect. [ABSTRACT FROM AUTHOR]

Under the influence of the dual policies of sustainable economic development and the national dual-carbon target, the establishment of an environmental protection department for the treatment of heavily polluting industries is imminent, and the country has launched pollution control policies and regulations to restrict the emission rights of heavily polluting industries. Therefore, this paper focuses on whether the restriction of emission rights in key industries has reduced carbon emissions. To achieve this, this paper uses panel data of prefecture-level cities in China from 2006 to 2019 and adopts a two-way fixed-effects DID model to systematically analyze the impact of the key pollution industry governance policies launched by the Ministry of Environmental Protection on CO2 emissions in 2017. And further analyze the role of variables such as green technology innovation patents and energy efficiency using this model, while parallel trend tests and placebo tests, and related policies are used to ensure the robustness of the regression results. This paper reveals that: (1) The heavy pollution industry governance policy implemented in 2017 can effectively reduce CO2 emissions in the cities of the treated group, and the effect is more significant in the year of policy implementation; (2) Green utility patents and energy-use efficiency are the effective mediating mechanisms to reduce CO2 emissions; (3) Over time, the effect of heavy pollution industry governance policy on CO2 emissions gradually decreases; (4) The reliability of the baseline regression results of this paper is proved by the use of parallel trend tests, placebo tests, and tests excluding the influence factors such as relevant policies in the same period. Therefore, the key polluting industries treatment policy launched by China's Ministry of Environmental Protection in 2017 under the recent dual-carbon policy development goals formulated by China, can effectively reduce carbon emissions; however, in the future economic development process, the government should give more consideration to the continuity of the policy impact and its coherence on economic development when implementing the policy. [ABSTRACT FROM AUTHOR]

In the political context of "carbon peaking" and "carbon neutrality" proposed by the Chinese government, this paper investigates the spatio-temporal evolution of land use transition in China after the implementation of the carbon emission trading scheme (CETS). Based on the analysis of the spatio-temporal evolution, we discuss the spatial spillover of the policy effects. With the help of China's CETS policy, this study explores the above issues with the main observation samples of the six provincial pilots included in CETS. Using the entropy weighting method, the indicator construction method, and local Moran's I test, this paper takes 30 provincial areas in China from 2010 to 2017 as the full sample, and draws the following conclusions: (1) both the economic and environmental effects generated by CETS can optimize land use transition in the pilot areas, but the effective time points of the two are different; (2) the time for land use transition to be optimized by the two effects of CETS is different, among which the economic effect takes effect faster than the environmental effect; and (3) there is spatial spillover of the optimization effect of CETS on land use transition, but the specific effect depends on the industrial structure and development plan of the pilot areas. [ABSTRACT FROM AUTHOR]

The development of green residences is crucial to reducing energy consumption and carbon emissions of the construction industry. However, the study on the spatial distribution characteristics of green residences and its influencing factors has not attracted enough attention in the academic circles. Base on the panel database on the number of each star green residences and their driving factors at the municipal level from 2008 to 2016, this paper employed the Weighted Standard Deviational Ellipse model to reveal the spatial and temporal evolution features of green residences in China, creatively introduced an improved Gini coefficient (G′-score) to measure the green residences development in each city, and utilized the panel Tobit model and average marginal effect to identify the driving mechanisms and key factors of green residences from economy, society, the real estate market, policy and climate. The main conclusions show that: (1) China has formed a relatively stable and clear temporal and spatial evolution path since 2011, such as the center of gravity and coverage having moved to the west, and the direction of development trend having weakened; (2) China's green residence is mainly distributed in the central and eastern regions, and the main direction layout is northeast–southwest; (3) the development of green residences is the result of the interaction of various factors, and the driving force of each factor varies greatly under the single action and the interaction; (4) the driving effects of the same factor on green residences with different star ratings are inconsistent in sign, magnitude, and significance, the same as for each factor under the same star rating. [ABSTRACT FROM AUTHOR]

This paper uses the entropy method to estimate China's green financial development from four aspects, namely, green credit, green securities, green insurance, and green investment, based on the provincial-level panel data from 2008 to 2019. The spatial Durbin model (SDM) is adopted to estimate the spatial effect of green finance on carbon emissions. We then compare the heterogeneous effect in the South and North of China. The results show that China's green financial development can significantly reduce carbon emissions, and regional heterogeneities are obvious. In the South of China, this effect from local and adjacent regions is not significant, while on the whole, green finance can significantly reduce carbon emissions; but for Northern China, this effect is not significant; nationally, the development of green finance and carbon emissions in adjacent areas showed an inverted U-shaped relationship. China's green financial development and carbon emissions also showed an inverted U-shaped relationship. These results suggest that the effect of green finance development on carbon emissions exhibits substantial regional heterogeneity in China. Our paper provides some concrete empirical evidence for policymakers to formulate green financial policies to achieve the double carbon goal in China. [ABSTRACT FROM AUTHOR]

Reducing agricultural emissions and promoting carbon sequestration are vital for China to achieve its dual carbon goals. Achieving the green transformation of agricultural watersheds requires a thorough understanding of the internal transmission relationships within the watersheds and the underlying spatial correlation structures. This paper used the SBM-3E model to calculate the agricultural ecological efficiency of 17 prefecture-level cities in the Hanjiang River Basin (HRB) from 2010 to 2020, taking agricultural carbon emissions and a comprehensive non-point source pollution index as the unexpected output. The Gravity model and social network analysis methods were used to analyze the evolution characteristics of the network structure of agricultural ecological efficiency, and the secondary assignment procedure method was used to identify the driving factors from the planting structure, water use structure, and resource endowment. First, from 2010 to 2020, the overall agricultural ecological efficiency in the HRB demonstrates a declining trend, with efficiency values of 12.15, 9.40, and 6.67 in the upper, middle, and lower reaches, respectively. Second, the spatial correlation network density of agricultural ecological efficiency in the HRB is 0.17, with a network efficiency of 0.89. The correlation among units within the basin is relatively low, but stability is high. Moreover, the individual network spillover absorption capacity exhibits heterogeneity, and the status of each subject within the watershed follows a "core-edge" structure. Third, total water consumption and corn cultivation have a positive impact on the agricultural ecological efficiency network in the HRB, whereas agricultural water use and rice cultivation negatively influence the network. We propose policy recommendations to facilitate the advancement of green development in China's agricultural watersheds and the achievement of the dual carbon goals. [ABSTRACT FROM AUTHOR]

China has made remarkable achievements in reducing carbon emissions in recent years. However, there is still much reduction room before achieving carbon neutrality. In Beijing, the capital of China, it is a strategic choice to respond to global climate change by promoting green and low-carbon development. This paper calculates the carbon dioxide emissions of key industries in Beijing and analyzes the temporal evolution trend of carbon emissions. Carbon dioxide emissions in Beijing before 2030 are predicted based on the grey prediction GM (1,1) and BP neural network model. The effects of factors of carbon dioxide emissions are discussed using the threshold regression model under different economic conditions. The results show that energy consumption intensity, GDP per capita, and the ownership of civil cars have a positive impact on carbon dioxide emissions, while the number of permanent residents and urban green space areas have a negative impact on carbon dioxide emissions. These findings of carbon emission prediction and influencing factors contribute to carbon reduction path design. Related policy implications on carbon emission reduction are put forward from the aspects of promoting industrial upgrading, accelerating the construction of advanced economic structures, optimizing transportation structures, and strengthening green building development. [ABSTRACT FROM AUTHOR]

The implementation of digital technology has become paramount to facilitating green and low-carbon development in dairy farms amidst the advent of digital agriculture and low-carbon agriculture. This study examined the impact of digital technology implementation on the carbon emission efficiency of Chinese dairy farms via an assessment of micro-survey data, incorporating an Undesirable Outputs-SBM model, a Tobit model, the propensity score matching technique, a quantile regression model, and an instrumental variable approach. This study examined the potential moderating influence of environmental regulations on digital technology applications and the carbon emission efficiency of dairy farms. The findings of the research indicate that the implementation of digital technology had a considerable beneficial consequence on the carbon emission proficiency of dairy farms. The statistical significance level of the mean treatment effect was 0.1161, with the most profound influence of precision feeding digital technology on the carbon emission efficiency in dairy farms. The application of digital technology has a more pronounced effect on dairy farms with lower levels of carbon emission efficiency compared to those with medium and high levels of carbon emission efficiency. The application of digital technology toward the carbon emission efficiency of dairy farms is positively moderated by environmental regulations. Finally, this paper puts forward some specific policy recommendations to achieve the strategic goal of low carbon and efficient development in dairy farms through the application of digital technology, which enriches the existing research on carbon emission reduction in dairy farms from theoretical and practical aspects. [ABSTRACT FROM AUTHOR]

China has pledged that it will strive to achieve peak carbon emission by 2030 and realize carbon neutrality by 2060, which has spurred renewed interest in hydrogen for widespread decarbonization of the economy. Hydrogen energy is an important secondary clean energy with the advantage of high density, high calorific value, rich reserves, extensive sources and high conversion efficiency that can be widely used in power generation, transportation, fuel and other fields. In recent years, with the guidance of policies and the progress of technology, China's hydrogen energy industry has developed rapidly. About 42% of China's carbon emissions comes from the power system and Shenzhen has the largest urban power grid in China. Bringing the utilization of hydrogen energy into Shenzhen's power system is an important method to achieve industry transformation, achieve the "double carbon" goal and promote sustainable development. This paper outlines the domestic and international development status of hydrogen energy, introduces the characteristics of Shenzhen new power system, the industrial utilization of hydrogen energy and the challenges of further integrating hydrogen energy into Shenzhen new power system and, finally, suggests on the integration of hydrogen energy into Shenzhen new power system in different dimensions. [ABSTRACT FROM AUTHOR]

In the context of tax sharing reform and land reform during the 1990s, local governments in China relied heavily on land finance. Local governments have fierce competition in attracting investment, omitting the development of green economy. Based on the data of industrial land sales and carbon dioxide emissions, this study constructed the panel data of 196 cities in China from 2007 to 2017 and analyzed the spatial and temporal evolution characteristics of urban industrial land price distortion and carbon emission intensity. Furthermore, a multiple linear regression model was constructed from the aspects of scale effect to empirically analyze the overall impact and differential impact of urban industrial land price distortion on carbon emission intensity. With the help of the mediating effect model, the mechanism of urban industrial land price distortion on carbon emission intensity was investigated from the perspective of industrial structure upgrading. The results showed that (1) the higher the price distortion of industrial land is, the more detrimental it is to the development of green and low-carbon economy. (2) The regional heterogeneity test showed that the impact of industrial land price distortion on carbon emission intensity is most significant in the central region, medium cities, and cities with low fiscal self-sufficiency rates, respectively. (3) The higher the distortion degree of industrial land price, the greater the restriction on the upgrading of industrial structure, further increasing the carbon emission intensity. This paper provides policy implications for the market-oriented reform of land factors and the realization of the "double carbon" goal. [ABSTRACT FROM AUTHOR]

China's economic development is characterized by openness, and trade and investment are important engines for promoting economic development. China's economy is now in a transitional period, during which excessive carbon emission reduction would inevitably hinder economic development. In this context, improving carbon emission efficiency is an effective way to achieve sustainable development. This paper deals with the relationships among foreign direct investment, technological innovation and carbon emission efficiency. Our research findings include the following. First, carbon efficiency shows regional differences. East China has the highest mean value of carbon emission efficiency, followed by central China and west China over the sample period. Second, FDI exerts both direct and indirect impacts on carbon emission efficiency through technological innovation, which confirms the intermediate effect of technological innovation. Finally, sub-sample analysis indicates that the impact of FDI and technological innovation on carbon emission efficiency show regional heterogeneity. According to these findings, we offer policy recommendations as follows. The government should stimulate independent innovation, promote technological progress in renewable energy and green energy, and attract environmentally friendly foreign investment to improve carbon emission efficiency and boost green development. [ABSTRACT FROM AUTHOR]

Land use change is closely related to the terrestrial ecosystem. Studying the relationship between land use and ecosystem service carbon storage under future climate change can optimize the regional ecosystem service function and formulate sustainable social and economic development policies, which is of great significance for regional carbon emission management and climate change response. In this paper, the coupled model of SSP-RCP-PLUS-InVEST was constructed to simulate land use change under different scenarios, analyze the influence degree of driving factors on different regions, and explore the spatio-temporal evolution and spatial correlation of carbon storage, taking Central Yunnan City agglomeration as an example. The results showed that: (1) from the perspective of land use change, the overall changes in SSP126 and SSP245 scenarios were similar, and the change rates of different types were slightly different. Under the SSP585 scenario, the forest area decreased, and the urban land and cropland land expanded. (2) Under the three scenarios in the future, the decrease in total carbon storage is the most serious under the SSP245 scenario, and the decrease is the most serious under the SSP585 scenario. (3) Comparative spatial correlation: the carbon storage in the Central Yunnan urban agglomeration is generally correlated among counties, and there is no significant difference under the future scenarios, showing a high accumulation pattern in the east and low accumulation pattern in the middle. In general, reasonable planning of land spatial patterns and increasing the proportion of forest is conducive to the proportion of regional carbon sequestration capacity. The research methods can provide references for addressing climate change and territorial spatial planning. [ABSTRACT FROM AUTHOR]

Land resources have become one of the major factors limiting urban development in China. In the context of sustainable development, how to improve land use efficiency (LUE) has become a major challenge on the road to sustainable development in China. Carbon finance provides a new idea for sustainable development. With the help of carbon emissions trading policy (CETP), this paper aims to investigate whether carbon finance can optimize LUE in terms of economic effects and environmental effects. Based on the data of 158 prefectural-level cities in China from 2010 to 2017, this paper uses a combination of qualitative and quantitative analysis to investigate these issues. Specifically, this paper measures the land use efficiency from economic effects (LUE_Eco) and environmental effects (LUE_Env) using the entropy method, and visualizes the data to obtain information on their spatio-temporal evolution patterns. Furthermore, this paper verifies the causal relationship between policy implementation and LUE_Eco and LUE_Env by using the difference in differences (DID) method. The conclusions show that: (1) the levels of LUE_Eco and LUE_Env in the pilot regions generally increase after the implementation of the CETP, but only the increase of LUE_Env is due to the policy implementation; (2) the CETP not only effectively reduces CO2 emissions, but also promotes the reduction of industrial 'three wastes' emissions. Accordingly, this paper has gained insights on how to improve LUE in China. [ABSTRACT FROM AUTHOR]

In recent years, China has increasingly emphasized green development. Therefore, it is of theoretical and practical significance to study the green economic effect and carbon reduction effect of tourism development for the transformation of economic development. Using the superefficient EBM to measure the green economic efficiency of 280 cities from 2007–2019, we rely on the spatial Durbin model to explore the spatial spillover utility and nonlinear characteristic relationship of tourism development on green economic efficiency and carbon emission intensity and test the mediating effect of carbon emission intensity. The findings are as follows: (1) Under the exogenous shock test of the "low-carbon city" pilot policy, the spatial spillover effect of tourism development on urban green economic efficiency and carbon emission intensity is robust to spatial heterogeneity. (2) The spatial spillover effects of tourism development on the green economic efficiency and carbon emission intensity of cities show a nonlinear characteristic relationship of "U" and "M" shapes. After tourism development reaches a certain high level, the green economy effect and carbon emission reduction effect are significantly increased. (3) Carbon emission intensity has a significant mediating effect on the impact of tourism development on urban green economic efficiency. [ABSTRACT FROM AUTHOR]

A growing number of countries worldwide have committed to achieving net zero emissions targets by around mid-century since the Paris Agreement. As the world's greatest carbon emitter and the largest developing economy, China has also set clear targets for carbon peaking by 2030 and carbon neutrality by 2060. Carbon-reduction AI applications promote the green economy. However, there is no comprehensive explanation of how AI affects carbon emissions. Based on panel data for 270 Chinese cities from 2011 to 2017, this study uses the Bartik method to quantify data on manufacturing firms and robots in China and demonstrates the effect of AI on carbon emissions. The results of the study indicate that (1) artificial intelligence has a significant inhibitory effect on carbon emission intensity; (2) the carbon emission reduction effect of AI is more significant in super- and megacities, large cities, and cities with better infrastructure and advanced technology, whereas it is not significant in small and medium cities, and cities with poor infrastructure and low technology level; (3) artificial intelligence reduces carbon emissions through optimizing industrial structure, enhancing information infrastructure, and improving green technology innovation. In order to achieve carbon peaking and carbon neutrality as quickly as possible during economic development, China should make greater efforts to apply AI in production and life, infrastructure construction, energy conservation, and emission reduction, particularly in developed cities. [ABSTRACT FROM AUTHOR]

Rapid urbanization and an increasing carbon footprint have underscored the need for sustainable practices in the construction industry. With the aim of prioritizing global sustainable development, the measurement of carbon emission efficiency in the construction industry (CEECI) has emerged as a critical indicator. Nevertheless, a comprehensive exploration of carbon emission efficiency within the Chinese construction sector remains limited, despite the pressing demand to mitigate carbon emissions. To address this research gap, this study aims to provide valuable policy recommendations for effectively reducing carbon emissions. We conducted a thorough assessment of both the total carbon emissions and the carbon emission intensity in 30 provinces and cities across China from 2010 to 2020. Utilizing the slacks-based measure (SBM) model with non-desired outputs, we evaluated the static CEECI, including the spatial correlation analysis and the evaluation of the carbon reduction potential in the construction industry (CRPCI). Additionally, the dynamic CEECI was quantified using the Malmquist–Luenberger (ML) index model, followed by an index decomposition analysis. The findings reveal several noteworthy insights: (1) There exists a positive correlation between carbon emissions in the construction industry and the economic scale. Generally, less developed areas (e.g., central and western regions of China) exhibit higher levels of carbon emission intensity (CEICI), while more developed areas (e.g., eastern regions of China) demonstrate lower levels of CEICI. (2) The CEECI across various provinces and cities demonstrates a clear spatial positive autocorrelation, while the CRPCI exhibits a negative correlation with the CEECI, with larger CRPCI values observed predominantly in western China. (3) Technological progress (MLTC) emerges as a crucial factor influencing the CEECI in our dynamic analysis. These findings offer valuable insights for policymakers to develop focused strategies to effectively mitigate carbon emissions nationwide. [ABSTRACT FROM AUTHOR]

Carbon neutrality is a key human endeavor to deal with global climate while China is the country producing the most publications on carbon neutrality. However, what are the focuses of carbon-neutrality research in China? To answer such an important question, this study adopts a bibliometric approach to analyze carbon-neutrality journal publications from China-based researchers during the period of 2008–2022 using CNKI and Scopus. Results showed that carbon-neutrality publications in Chinese and English journals by Chinese-based researchers increased from 4 in 2008 to 2879 in 2022. In Chinese journals, X.D. Hao was the most productive author with 10 publications. In English journals, Y.K. Zhou was the most productive author with 14 publications. As a whole, the Chinese Academy of Sciences was the most productive institution with 376 publications. Co-occurrence of keywords analysis revealed seven themes in Chinese journal articles, namely, "carbon neutrality and climate change", "energy transformation", "peak carbon emission", "carbon emission and low carbon economy", "realization path in China", "hydrogen energy and clean energy", and "green finance and sustainable development". In English journals, three major clusters were formed—"carbon, carbon neutralities, emission control, and energy utilization", "carbon dioxide, carbon neutrals, biomass, and electrocatalysts", and "China, carbon neutrality, sustainable development, and economic development." Most extant publications focused on policy and technological development. Emphasis shall be paid to social change and changes in people's behavior, sectoral carbon emissions, and carbon leakage in future research. [ABSTRACT FROM AUTHOR]

For a healthy industrial structure (IS) and stable economic development in China, this study proposes an improved link prediction algorithm (LP) based on complex networks. The algorithm calculates the similarity by constructing a mixed similarity index. A regional IS network model is built in the study, and the direction of IS adjustment is calculated with the mixed similarity indicators. In this study, the prediction accuracy of the proposed improved LP algorithm in the real network dataset is up to 0.944, which is significantly higher than that of the other algorithms. In the reality of IS optimization, industries of high similarity could be obtained through similarity algorithms, and reasonable coordinated development strategies are proposed. In addition, the simulated IS adjustment strategy in this study shows that it is highly sustainable in development, which is reflected in its lower carbon emissions. The optimization of IS adjustment could be achieved through IS network model and the improved LP algorithm. This study provides valuable suggestions for China's regional industrial structure adjustment. [ABSTRACT FROM AUTHOR]

For years, China has adopted environmental regulations in developing ports to improve their sustainability. Based on the data of Chinese ports from 2009 to 2018, this paper presents a data envelopment analysis model with subdividing input-output indicator weights and develops it further in two stages with the weight preference and the slacks-based measure, respectively. After assessing the sustainable development capability (SDC) of Chinese ports and their spatial correlation, it revealed that Chinese ports are clustered in several regions and their SDC has spilled over into their neighbors. Further study revealed the SDC is affected by environmental regulations in different ways: as a key measure among regulations to improve the SDC, voluntary regulation has a spatial spillover effect, but neither the mandatory regulation nor public media regulation can significantly improve the SDC. This suggests that the port authority should enact environmental regulations based on the port spatial difference and the port should expand its operation scale and market size and recruit more top talent, which is good for improving its productivity and reducing its carbon emissions. [ABSTRACT FROM AUTHOR]

Petroleum agriculture, characterized by mechanization and chemistry, is developing rapidly in China. However, petroleum agriculture has not only brought food safety problems, but also caused great obstacles to the sustainable development of society. In view of the disadvantages of oil agriculture, we provide an upgrading plan for energy systems in agriculture. This work can help reduce carbon emissions and improve food security. We introduce the most advanced technologies in Chinese agricultural development and the technical scope includes new agricultural energy power generation, agricultural energy use and the safe operation of agricultural energy systems. We describe the detailed data of agricultural bioenvironmental and energy engineering to clarify the level of agricultural energy efficiency in China. The overall conclusion of this paper is that the deep integration of agriculture and energy internet has become the development trend of agricultural energy systems. [ABSTRACT FROM AUTHOR]

Industry is widely valued as an important contributor to carbon emissions. Therefore, it is of great significance to analyze the industrial carbon emissions (ICE) in Guangdong, the strongest industrial province in China. We have adopted the carbon emission accounting model and standard deviational ellipse analysis model to analyze the temporal and spatial characteristics and evolution trends of the industry carbon emission amount and intensity in Guangdong from 1998 to 2013. The study results include: (1) Due to the rapid development of industry, Guangdong's ICE showed a steady growth trend; (2) The distribution characteristics of ICE were characterized by the trend of taking the Pearl River Delta (PRD) region as the center and gradually spreading to the surrounding areas. From the perspective of industrial sectors, it can be divided into steady growth type, fluctuant growth type, basically stable type, and decrease type; (3) The spatial pattern of the ICE in Guangdong is basically the same as that of the total industrial output value, that is, the southwest-northeast pattern. This work is helpful for China's carbon peak, especially for the formulation of industrial carbon peak policy and the sustainable development of the environment. [ABSTRACT FROM AUTHOR]

Against the background of continuously rising energy carbon emissions, accelerated energy transformation in developed countries, and increased international attention to energy security, there is still a large amount of energy consumption in the manufacturing industry. Promoting the diffusion of green supply-chain management is becoming a powerful tool to support energy transformation and energy conservation and emission reduction in the manufacturing industry. Based on this, we first conducted a scientific metrological analysis of 4960 articles in relevant fields in the Web of Science database, presenting the research status of green supply-chain management diffusion in the context of energy transformation. Second, we identified factors that affect the implementation of green supply-chain management, and analyzed the diffusion path of green supply-chain management among enterprises. Finally, based on the energy situation, enterprise operation, and implementation of environmental protection laws and regulations in Shaanxi Province, China, we determined the current situation, obstacles, and development direction of green supply-chain management diffusion of enterprises in the context of energy transformation. The research found that: at this stage, there are still some deficiencies in the research on the mechanism of green supply-chain management in the internal communication of enterprises; in the future, the diffusion of green supply-chain management can be further developed around social performance and energy transformation technology; and we can help energy transformation by strengthening policy guidance and assisting enterprise reform. [ABSTRACT FROM AUTHOR]

Modern agriculture contributes significantly to greenhouse gas emissions. How to reduce such emissions without sacrificing agricultural development is a common issue concerning most developing countries. In China, a rural revitalization strategy proposed in 2018 aims to achieve agricultural modernization by 2050, while reaching a carbon emission peak by 2030 and neutrality by 2060. However, China's progress towards these goals is largely unknown. This study evaluates the coupling coordination and spatiotemporal dynamic evolution between agricultural carbon emissions and agricultural modernization in China from 2010 to 2020 through a joint employment of spatial autocorrelation and coupling coordination degree modeling. The results show that from 2010 to 2020, the agricultural modernization level increased from 0.155 to 0.272, and the agricultural carbon emission intensity decreased from 4.9 tons per 10 thousand CNY to 2.43 tons. Agricultural carbon emissions and the agricultural modernization level manifest significant spatially agglomerative patterns with noticeable discrepancies across different regions. Moreover, the coupling coordination degree between agricultural carbon emissions and agricultural modernization has increased every year, but disparities among provinces continued to widen. Specifically, coupling coordination in northern China is significantly higher than that in the south, and its spatial distribution exhibits a positive correlation and increasing levels of clustering. These results point to the continued need for sustainable agricultural development efforts, such as strengthening rural infrastructure and diffusing green technologies in achieving China's dual carbon emission and agricultural modernization goals. This study also examines the sustainable agricultural development issue from a new perspective, and the findings can provide policy references for sustainable agricultural development policies in China. [ABSTRACT FROM AUTHOR]

In order to mitigate the negative effects of global climate change, the Chinese government has committed to achieving peak carbon emissions by 2030 and carbon neutrality by 2060. Since municipal cities are the bottom administrative level for drawing up development plans, it is necessary and important to conduct decarbonization pathway research on municipal energy systems (MESs). However, there is little research on decarbonization at the municipal level, and the impact of development paths in each forecast scenario is mostly based on expert evaluation and qualitative assessment. Therefore, this study established a complete decarbonization framework for MESs, including general research procedures, models, and a sustainable evaluation method. The models of energy consumption and carbon emission were adapted and improved for MESs. In order to quantitatively evaluate the energy system development for each scenario, we proposed an energy–economy–environment–security (3E–S) evaluation method, in which principal component analysis (PCA) was adopted for multi-criterion decision making. According to the analysis results of the case city in Guangdong, this evaluation method was proved to be an effective way to identify the factors that may influence coordinated development. By adjusting the relevant parameters and factors in the model, the optimal decarbonization pathway can be found to promote sustainable and coordinated development, thus helping government decision makers to quantitatively evaluate planning paths. [ABSTRACT FROM AUTHOR]

Carbon emissions have become a serious environmental problem worldwide, with the greenhouse effect and global temperature increase being the main areas of concern. Financial inclusion is a means to increase the welfare of citizens and promote sustainable development. Development of financial inclusion may have a big impact on carbon emissions. This study uses data from 2011 to 2019 to do panel Tobit regression and check the effect of financial inclusion on the efficiency of carbon emissions, which is calculated by the super-efficiency Slacks-Based Measure (SBM) -data envelopment analysis (DEA) method. The results show that financial inclusion decreases the efficiency of carbon emissions. Moreover, financial inclusion could reduce the efficiency of carbon emissions by increasing the proportion of tertiary industries. Moreover, the effect varies in each region. Thus, following these conclusions, we propose several related policy implications. The government should strengthen the supervision of money due to financial inclusion and ensure that the investment should be put into environmental projects. In addition, it needs to pay attention to carbon emissions generated in the process of industrial upgrading. More access to renewable energy is an effective measure to solve the problem of higher carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Carbon emission reduction is a systematic project requiring support from policy, capital, and technology in its promotion, which represents a greater need for green finance. Frontier research focuses on the impact of green finance on local CO2 emissions, but generally ignores its ripple impacts on carbon emission reduction in adjacent areas. Combining panel data from 30 Chinese provincial-level cities from 2004 to 2019, this study employs a spatial panel Durbin model to empirically test the ripple effect of green finance on carbon emission reduction in adjacent areas and further investigate the formation mechanism of the ripple effect. The results are as follows: (1) Green financial development has a significant inhibitory effect on local and neighboring CO2 emissions, which affirms the existence of the ripple effect of green finance. (2) Through formation mechanism analysis, it is found that the upgrading of an industrial structure has played a transmission role in the ripple effect of green finance. Finally, based on the empirical results, some suggestions are put forward from the perspectives of innovating green financial services and promoting the effective alignment of green financial development with carbon emission reduction targets and the deep integration of green finance and regional green industry development, so as to better develop the potential of green finance in the realization of the carbon reduction goals. [ABSTRACT FROM AUTHOR]

The carbon emissions in China contribute to around one-third of the world total. Therefore, China plays a critical role in global carbon emissions reduction. Over the last few years, the Chinese government has implemented a range of counter-measures to accelerate the green transition. In this research, we empirically investigate the relationship between carbon intensity and the green transition. Based on provincial panel data of Chinese manufacturing industries from 2008 to 2019, we measure the relationship between carbon intensity and green transition capacity in 30 provinces, employing the Generalized Method of Moments (GMM) to examine their influencing mechanism and regional heterogeneity. Furthermore, we use an intermediary model to investigate the influence of financial development on the relationship between carbon intensity and manufacturing green transition. We find that a U-shaped relationship exists, where increasing carbon emissions restrain the green transition initially but improve it later, such that the transition upgrades gradually. Regarding the regional heterogeneity, the GMM results show that carbon intensity has the most significant impact on the green transition in the central provinces, followed by western provinces. Meanwhile, financial performance is an essential contributor to the relationship, as more funds flow into contamination-dominated but profitable projects, thus inhibiting the transition. Urbanization and marketization are also included into threshold models, which suggest the existence of relevant threshold effects in the relationship. These findings have a referenced value suggesting that the local governments follow the U-shaped theory to reform the local carbon reduction policies and green development target according to the regional economic performance and geographical advantages. [ABSTRACT FROM AUTHOR]

Renewable energy consumption is considered as the main form of energy consumption in the future. The carbon emissions produced by renewable energy can be approximately ignored, and renewable energy is essential for regional sustainable development. In this study, we used the Durbin model with panel data to explore the spatial dependence between renewable energy consumption the and carbon emissions of China's 30 provinces from 1997 to 2017. The results show that: (1) there is a negative spatial correlation between renewable energy consumption and carbon emissions, and "High-Low" areas are mainly concentrated in southern provinces in 1997–2011; (2) the center of gravity of renewable energy consumption moves southwest, which is consistent with the center of gravity of carbon emissions; (3) renewable energy consumption has a significant inhibitory effect on carbon emissions of a local region, but the spatial spillover effect is not significant. Specifically, a 1% increase in renewable energy consumption in a region will reduce carbon emissions by 0.05%. Finally, on the basis of this study, it was proposed to give full play to the advantages of renewable energy in the western region, and further accelerate the development of the renewable energy industry. [ABSTRACT FROM AUTHOR]

Human activities have increased greenhouse gas emissions since the Industrial Revolution, and "emission peaking" and "carbon neutrality" have become serious concerns at this point. The role of information infrastructure in reducing carbon emissions is a critical issue that has received little attention and needs to be addressed. Using panel data from 289 cities in China between 2011 and 2017, this research empirically explores the impact of information infrastructure on urban carbon emission intensity and the mechanism behind this effect. We discover that the construction of information infrastructure significantly reduces urban carbon emissions, and this finding holds true after a series of robustness tests. The mechanism is optimization of industrial structure, agglomeration of producer service industries, and innovation of green technologies. According to the heterogeneity test, the carbon emission reduction is greater in mega cities with higher technological levels and larger urban scales, as well as large cities with better traditional infrastructure. The present work's findings give empirical support for promoting green and low-carbon development and mitigating global warming. [ABSTRACT FROM AUTHOR]

Under the "double carbon" target, it is important to reduce carbon emissions in each region. Using exploratory spatial data analysis (ESDA), the center of gravity method, and spatial econometric models, we analyzed the characteristics and spatial spillover effects of carbon emission intensity in counties in Northeast China from 2000 to 2020 and made recommendations to the government for more reasonable carbon reduction strategies in order to achieve sustainable development. The results were as follows: (1) Since 2000, the carbon emission intensity in Northeast China has increased after first declining, and the carbon emission intensity in the western and northern regions of Northeast China has increased faster than Northeast China's average. (2) After 2000, the spatial aggregation of carbon emission intensity has improved in Northeast China. (3) Northeast China's carbon emission intensity has a positive spatial spillover effect. Through the feedback mechanism, the growth in population size, the rise in economic development level, the level of industrialization as well as the rise in living standard, the land use structure dominated by arable land and construction land, and the increase in urbanization level in the region will cause the carbon emission intensity in the surrounding areas to increase. An increase in public expenditures leads to a decrease in carbon emission intensity in the adjacent area. (4) When the vegetation cover exceeds its threshold value, it can have a larger inhibitory influence on carbon emission intensity. To summarize, each county in Northeast China is a carbon emission reduction community, and policymakers must consider the spatial spillover effect of carbon emission intensity when developing policies. [ABSTRACT FROM AUTHOR]

Agricultural ecological efficiency is not only the key link between green development and high-quality development of agriculture, but also an important regulatory indicator for China's rural revitalization. Based on provincial panel data of China from 2000 to 2019, using land, mechanical, labor, fertilizer, pesticide, and agricultural film as input variables and economic output and agricultural carbon emissions as output variables, the inter-provincial agricultural ecological efficiency is calculated by a super-efficient SBM model, and the traditional spatial Markov probability transfer matrices are constructed based on time series and spatial correlation analyses. By exploring the spatial and temporal dynamic evolution characteristics of agricultural ecological efficiency, it is found that the agricultural ecological efficiency of China increased steadily with fluctuations. In addition, the provincial gap has been narrowing, but the overall level is still at a low level; thus, there is still a large space for improvement in agricultural ecological efficiency. The overall trend of agricultural ecological efficiency shifting to a high level in China is significant, but its evolution has the stability to maintain the original state, and achieving leapfrog transfer is relatively hard. The geospatial pattern plays an important role in the spatial-temporal evolution of agricultural ecological efficiency, with significant spatial agglomeration characteristics. Provinces with high agricultural ecological efficiency enjoy positive spillover effects, while provinces with low agricultural ecological efficiency have negative spillover effects; thus, gradually forming a "club convergence" phenomenon of "high agglomeration, low agglomeration, high radiation, and low suppression" in the spatial pattern. In addition, support for the improvement of agricultural ecological efficiency will be provided in this study. [ABSTRACT FROM AUTHOR]

Southwest China faces harsh environmental pollution challenges and rapid development. Against this backdrop, exploring the impact mechanism of the urban network on carbon emissions in rapidly developing regions is of great significance to the balance between regional development and carbon emissions reduction, as well as regional sustainable development. The objective of this study is to quantify the relationship between carbon emissions and the urban network, using panel data analysis for 47 cities in southwest China from 2010 to 2019. Therefore, several urban network indices were selected and quantitatively studied by using the spatial Durbin model to reveal the impact mechanism of the urban network on carbon emissions in rapidly developing regions. The results show that: (1) the growth of carbon emissions in a city has a significant positive spatial spillover effect on the surrounding areas; (2) the temporal and spatial distribution of carbon emissions is highly coincident with the urban network; (3) the urban network has a two-sided impact mechanism of promoting and inhibiting carbon emissions; and (4) the effect of the impact mechanism is affected by regional development conditions, and the promotion effect plays the main role in rapidly developing regions. [ABSTRACT FROM AUTHOR]

Standardization in energy-saving and emission-reduction measures has become increasingly important. The impact of standardization on carbon-emission efficiency in China was explored by using panel data from 2002 to 2017. The results showed that standardization significantly improved China's carbon-emission efficiency, which remained robust after a series of tests. Furthermore, the development of industry standards had a greater effect on the improvement of carbon-emission efficiency in the economically developed coastal areas, while the development of national standards significantly promoted the improvement of carbon-emission efficiency in the inland areas. An assessment of the impact mechanism demonstrated that standardization affects carbon-emission efficiency through technological progress, industrial modernization, and economies of scale. We compared our findings with the existing literature regarding the governance of a low-carbon economy; we also considered the subsequent policy implications of our findings in terms of sustainable economic development. [ABSTRACT FROM AUTHOR]

Space utilization and climate change are related to human survival and development. Identifying the relationship between development and conservation is the foundation of sustainable development. We used the kernel density curve, spatial analysis, and the sensitivity model to study the spatial use efficiency and carbon emissions evolution characteristics at the provincial and regional levels in China from 1999 to 2019. The results show that a trend of high efficiency and low carbon emissions in southeast coastal cities and towns is gradually forming, and agricultural spaces are moving toward high efficiency and high carbon emissions patterns. The evolution paths of space utilization efficiency and carbon emissions differ significantly across spaces and regions. We also found similarities in how carbon emissions intensity responds to changes in spatial utilization efficiency in the Yangtze and Yellow River basin urban agglomeration. The study provides practical suggestions for the high-quality development of territorial space, ecological environment management, and sustainable development in light of spatiotemporal changes. [ABSTRACT FROM AUTHOR]

Climate change has gained widespread attention, and the rapid growth of the economy in China has generated a considerable amount of carbon emissions. Zhejiang Province was selected as a study area. First, the energy-related carbon emissions from 2000 to 2014 were accounted for, and then the Logarithmic Mean Divisia Index (LMDI) decomposition model was applied to analyse the driving factors underlying the carbon emissions. Finally, three scenarios (inertia, comparative decoupling and absolute decoupling) for 2020 and 2030 were simulated based on the low-carbon city and Human Impact Population Affluence Technology (IPAT) models. The results showed (1) carbon emissions increased by 1.66 times from 2000 to 2014, and trends of carbon emissions were used to divide the study period into three phases (rapid, medium growth and slow decrease phases, with annual growth rates of 12.60%, 4.77% and -1.24%, respectively); (2) the energy intensity effect from 2000-2011 inhibited carbon emissions but was exceeded by the economic output effect, which increased emissions, whereas the energy intensity effect from 2011-2014 outweighed the economic output effect; (3) the scenario analyses revealed that both the comparative and absolute decoupling scenarios would remain consistent with the carbon emissions boundaries in 2020 and 2030, but the comparative decoupling scenario was more reasonable for sustainable development. In addition, appropriate design of emission trading scheme could help to achieve the comparative decoupling by financial incentives. [ABSTRACT FROM AUTHOR]

This study aimed to understand green finance's impact on fertilizer use and agricultural carbon emissions. We selected the macro panel data of 30 provinces (cities) in China from 2000 to 2019. The main research methods are standardized test framework (cross-sectional dependence, unit root and cointegration test), the latest causal test, impulse response, and variance decomposition analysis. Examined the long-term equilibrium relationship between green finance, fertilizer use, and agricultural carbon emissions. The results show: fertilizer consumption and agricultural carbon emissions have a positive correlation. However, green finance can significantly reduce agricultural carbon emissions. The causal test confirmed the bidirectional causal relationship between agricultural carbon emissions and fertilizer use. At the same time, verified one-way causality from green finance to both of them. Interpret the results of impulse response and variance decomposition analysis: among the changes in agricultural carbon emissions, chemical fertilizers contributed 2.45%, green finance contributed 4.34%. In addition, the contribution rate of green finance to chemical fertilizer changes reached 11.37%. Green finance will make a huge contribution to reducing fertilizer use and agricultural carbon emissions within a decade. The research conclusions provide an important scientific basis for China's provinces (cities) to formulate carbon emission reduction policies. China has initially formed a policy system and market environment to support the development of green finance, in 2020, the "dual carbon" goal was formally proposed. In 2021, the national "14th Five-Year Plan" and the 2035 Vision Goals emphasized the importance of green finance. It plays an important supporting role in carbon emission reduction goals, and green finance has become an important pillar of national strategic goals. [ABSTRACT FROM AUTHOR]

Based on the background of China's "carbon neutral" policy and the booming digitalization, how does environmental regulation affect green economy performance? The existing literature has studied the impact of energy consumption on green economic performance. However, the literature has ignored the impact of carbon dioxide emissions on China's green economy performance. In this regard, this research uses the non-radial distance function (NDDF) to calculate the green economic performance of China's prefecture-level cities, and uses the dynamic panel threshold model and the systematic GMM method to study the nonlinear impacts and mechanisms of environmental regulation, digital development, technological innovation, and industrial structure upgrade on green economic performance. The panel data set contains 228 Chinese cities from 2003 to 2019. The following findings are established: first, after adding carbon dioxide emissions to China's green economy performance, the environmental performance was reduced, and the green economy performance was also reduced. Second, the impact of environmental regulations on green economic performance has a double-threshold effect, with threshold values of −0.267 and 3.602, and this double-threshold effect has temporal and regional heterogeneity. Third, environmental regulations of different intensities have a single-threshold effect between digital development, technological innovation, and industrial structure upgrade, with threshold values of 2.955, 3.957, and 2.249, respectively. Fourth, digital development, technological innovation, and industrial structure upgrade promote green economic performance. Fifth, environmental regulation acts on green economic performance through the transmission of digitalization, technological innovation, and industrial structure upgrade. Based on these empirical findings, this research suggests that Chinese local governments should appropriately increase the intensity of environmental regulations, strengthen the digital application and technological innovation, and promote the upgrading of industrial structure to achieve the improvement of urban green economic performance. [ABSTRACT FROM AUTHOR]