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To gain a deeper understanding of the intrinsic dynamic relationship between energy consumption and economic growth in China. This study employs panel cointegration and causality models, utilizing the SYS-GMM technique to assess the factors influencing economic growth in China's green finance sector from 2002 to 2022. The research explores the interactions among multiple variables related to the Chinese economic context, including economic growth, carbon dioxide emissions, total natural resource rents, energy consumption, and environmental impact. While considering key factors that may cause structural disturbances in the time series analysis. The findings indicate the existence of long-term cointegration relationships among these variables, with positive correlations between economic growth and total natural resource rents, energy consumption, energy quantity, and ecological footprint. Results also show a bidirectional causal relationship between carbon dioxide emissions and energy consumption and a unidirectional correlation between energy consumption and GDP growth. Additionally, energy intensity (EI) improvements supported by green finance are linked to a significant reduction in CO2 emissions, with a coefficient of -1.933 (p < 0.05), underscoring the role of technological innovation. Further evaluations suggest that investments in renewable energy can promote economic growth, create job opportunities, and reduce greenhouse gas emissions. Energy-saving measures and green finance-supported technological innovations play crucial roles in improving energy intensity and reducing CO2 emissions. The study also underscores the importance of economic diversification to reduce dependence on natural resources and enhance economic stability. Future research should further explore the economic feasibility and environmental benefits of emerging technologies such as Carbon Capture and Storage (CCS), providing deeper insights into sustainable energy practices. [ABSTRACT FROM AUTHOR]

This study aims to analysis the influence of economic growth (EG) and energy consumption (EC) on sulfur dioxide emissions (SE) in China. Accordingly, this study explores the link between EG, EC, and SE for 30 provinces in China over the span of 2000e2019. This study also analyzes cross-sectional dependence tests, panel unit root tests, Westerlund panel cointegration tests, Dumitrescu-Hurlin (D-H) causality tests. According to the test results, there is an inverted U-shaped association between EG and SE, and the assumption of the Environmental Kuznets Curve (EKC) is verified. The signs of EG and EC in the fixed effect (FE) and random effect (RE) methods are in line with those in the dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS) and autoregressive distributed lag (ARDL) estimators. Moreover, the results verified that EC can obviously positive impact the SE. To reduce SE in China, government and policymakers can improve air quality by developing cleaner energy sources and improving energy efficiency. This requires the comprehensive use of policies, regulations, economic incentives, and public participation to promote sustainable development. [ABSTRACT FROM AUTHOR]

Chinese cities are pursuing an energy transition to decouple energy-related carbon emissions (ERCEs) from economic growth. Despite numerous studies focusing on the factors influencing carbon emissions, few have quantitatively analyzed their respective contribution rates, thus leaving a gap in effectively guiding policies. This study took 16 cities in the Yangtze River Delta (YRD) as the study area. The decoupling between ERCEs and economic growth was analyzed during 2000–2020, and the contribution rates of different factors were explored. The results showed that the total ERCEs increased from 413.40 million to 1265.86 million tons during 2000–2020, increasing by over three times. Coal and oil were the dominant energy sources in most cities, but natural gas consumption increased from 0.15% to 5.96%. Moreover, 14 cities showed a decoupling status, indicating a certain win–win situation between economic growth and ERCE reduction. Economic growth greatly increased ERCEs, with its contribution rate ranging from 114.65% to 493.27% during 2000–2020. On the contrary, energy structure and energy intensity both contributed to reducing ERCEs in most cities, and their maximum contribution rates reached −32.29% and −449.13%, respectively, which were the main forces for the win–win situation. Finally, carbon reduction proposals are put forward, which provide theoretical support for achieving the "Double Carbon" goal in the YRD. [ABSTRACT FROM AUTHOR]

In today's highly advanced industrialised and modernised world, China's economy is still growing, and its demand for energy is increasing daily. It is crucial to examine the connection between energy consumption, carbon emissions, and economic growth in order to promote economic growth based on energy conservation and emission reduction. Using Dezhou City in Shandong Province as an example, the study builds a VAR model of carbon emission, energy consumption, and economic growth in Dezhou City based on simplified macroeconomic sub-models, energy sub-models, and environmental sub-models. It then determines the correlation and influence mechanism between the three using tests like ADF unit root and Granger causality. The pertinent elements affecting Dezhou's carbon emissions were then investigated using grey correlation analysis. Finally, based on the study's findings, policy suggestions are made regarding energy use, carbon emissions, and economic expansion. It is necessary not only to restrain high-energy consumption industries and fundamentally optimize the energy consumption structure, but also to find new economic growth points and improve economic growth channels, so as to optimize the industrial structure. In this process, increasing the proportion of the tertiary industry is a key measure. In addition, the government needs to advocate the citizens to adopt a low-carbon lifestyle, and the concept of low-carbon environmental protection will be deeply rooted in the hearts of the people. This study will provide suggestions and theoretical guidance for China's energy consumption and carbon emissions, and help achieve high-quality growth of China and even the world economy. [ABSTRACT FROM AUTHOR]

The unavoidable option for socially sustainable development is a low-carbon economy. One of the essential steps for China to attain high-quality development is reducing carbon emissions. It is necessary to realize low-carbon development in Sichuan, as it is not only an important economic zone but also an ecological protected area. The concurrent relationship among energy consumption, carbon emissions, and economic growth was examined in this study using the Tapio decoupling indicator, and the factors affecting energy consumption and carbon emissions in Sichuan were broken down using the logarithmic mean Divisia indicator (LMDI). The findings demonstrate a fundamental relative decoupling relationship between Sichuan's energy use and carbon emissions. Analysis of energy consumption and carbon emissions in Sichuan Province from 2005 to 2020 shows distinct patterns. From 2005 to 2012, in 2014, and from 2016 to 2020, the relationship between energy use and carbon emissions was relatively decoupled, with decoupling values ranging between 0 and 1. Absolute decoupling occurred in specific years: 2010, from 2013 to 2018, and in 2020. These periods are characterized by economic growth alongside reductions in carbon emissions. Factors affecting energy consumption and carbon emissions were consistently analyzed, showing similar impacts throughout the study periods. We find that population and economic growth are the main driving forces of these effects. The effects of energy intensity and industrial structure mainly play restraining roles, and the latter has a slightly weaker effect than the former. [ABSTRACT FROM AUTHOR]

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development. [ABSTRACT FROM AUTHOR]

R&D spending upsurges technological advancement and innovation which results in lowering energy consumption and environmental degradation. The current study investigates the asymmetrical impact of R&D spending on CO2 emissions in China via employing annual data from 1980 to 2021 and the NARDL model for empirical analysis. The estimated results of the NARDL model confirmed that there are asymmetries in positive and negative coefficients of R&D spending in China. The results depict that the positive shock in R&D spending exerts a negative and statistically significant impact on CO2 emissions in both runs implying that an increase in R&D spending lowers CO2 emissions. However, the negative coefficient of R&D spending yields a positive and statistically significant impact on CO2 emissions revealing the fact that a negative shock in R&D spending results in the upsurge of CO2 emissions in China. According to these findings, the impact of positive and negative shocks in R&D spending on CO2 emissions is asymmetric. The findings also show that the impact of a negative shock in R&D spending is greater than the impact of a positive shock on CO2 emissions. In addition to the negative shock in R&D spending, increases in energy consumption, economic growth, and FDI inflows also contribute to an upsurge in CO2 emissions in China. The robustness of the estimated results is assessed using standard fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models. The FMOLS and DOLS results have been confirmed to be sound and consistent with the results of the NARDL model. The study suggests that the economic strategies should aim at investing in R&D spending to foster environment-friendly technological innovations and to lower environmental degradation in China. [ABSTRACT FROM AUTHOR]

The carbon emissions trading system (CETS) is a helpful policy instrument for separating carbon emissions from economic expansion, and it significantly impacts energy efficiency (EE). This study uses 30 Chinese provinces from 2007 to 2020 as its research samples, and classifies energy efficiency into single-factor energy efficiency (SFE) and total-factor energy efficiency (TFE), using the difference-in-differences model to examine the effect and mechanism of the CETS on EE. As an additional tool to assess the efficacy of the CETS, the corresponding evolution of the rebound effect of energy-related carbon emissions (RECE) is also calculated. This study shows that the CETS can significantly improve EE in China's pilot provinces. The influence mechanism indicates that the effect of the CETS on EE is influenced by the level of government governance, green innovation, and industrial structure optimization. Further study finds that after the CETS was carried out, the RECE in pilot provinces was higher than that in non-pilot provinces, and 31.4% of carbon emissions reduced by EE improvement rebounded. Therefore, the CETS has yet to realize its full carbon reduction potential. The study offers specific policy proposals for the enhancement of China's CETS in light of the aforementioned findings. [ABSTRACT FROM AUTHOR]

Accelerating the low-carbon transformation of the energy consumption structure is an important way to realize Chinese-style green modernization and development. Given the specificity of China's resource endowment and regional differences in energy distribution, the degree of reliance on coal varies greatly from region to region. Therefore, the differential impact of this dependence on the low-carbon transformation of the energy structure deserves high attention. To systematically assess the impact of environmental target constraints on the low-carbon transformation of the energy consumption structure in coal resource-dependent regions, this study was conducted on the basis of a theoretical analysis of the intrinsic influence of environmental target constraints on the regional energy consumption structure as well as the regulating mechanisms played by economic growth pressures and green finance. Taking the environmental target constraint system with Chinese characteristics as a quasi-natural experiment and the panel data of 30 provinces in China from 2003 to 2020 as a sample, the study used a generalized difference-in-differences model to empirically test the impact of environmental target constraints on the low-carbon transition of the regional energy consumption structure, and discussed the moderating roles of the pressure of economic growth and green finance on this impact. The results showed that: (J) After the implementation of the environmental target constraint system, the energy consumption structure of coal resource-dependent regions deteriorated significantly compared with that of non-coal resource-dependent regions, which supported the existence of the ' green paradox' phenomenon. This conclusion remained robust after considering the impact of related policies and the use of synthetic instrumental variables to deal with the endogeneity problem. © The test of the impact mechanisms showed that in coal resource-dependent areas, local governments were more motivated to promote the low-carbon transformation of the energy consumption structure under the pressure of the ' dual targets' of environmental target constraints and the economic growth target. Affected by the level of financial regulation and the ' green-washing' behavior of enterprises, green finance exacerbated the dilemmas of energy transformation in coal resource-dependent areas. © An expansive analysis based on the regional market environment showed that the inhibitory effect of environmental target constraints on the low-carbon transition of the energy consumption structure was more prominent in regions with low marketization levels than in those with high marketization levels. The study suggests attaching great importance to the structural adjustment of energy consumption in coal resource-dependent regions and promoting the low-carbon transformation of the energy structure in an orderly manner according to local conditions. Meanwhile, the study also highlights the importance of taking ' green' as a defining feature of local economic growth and leading local economic growth with the green development concept. In addition, a scientific and efficient green financial regulatory system should be built to ensure that green financial funds are truly used for green and low-carbon projects. It is also necessary to improve the market-based environmental regulatory mechanism to create a favorable business environment. [ABSTRACT FROM AUTHOR]

Intelligence relieving energy consumption and economic growth nexus is important for green development. To explore the potential power for sustainability, this paper uses entropy weight method to measure the intelligent level, adopts decoupling indicator between energy consumption and economic growth for green growth performance, and builds a spatial model to diagnose the mechanism of decoupling system. The results show that the achievements of intelligent development in the three regions are remarkable, and the intelligent level in the eastern region is the most prominent of all. Regardless of regional differences, intelligence is the main and stable driver deepening decoupling indicator; Notable pushing-out or pushing-in spilling power on regional decoupling through many channels can be identified, namely urbanization, income and FDI. Clean energy can help promote the driving effects of intelligence on decoupling and is not confined by regions. The fierce green competition race in the form of "anti-typicality" mode exists in various regions, especially in the Western region; only in the Middle region, the intelligent spatial spillover effect can form the driving force for decoupling. Accelerating the intelligent development and the application of clean energy is an effective measure to achieve the green environmental targets. [ABSTRACT FROM AUTHOR]

Since its reform and opening, the Chinese economy has witnessed unprecedented development. This long-term high-speed development has significantly impacted the environment. In the process of energy development and consumption, the environment has been severely polluted, and greenhouse emissions have increased. This has resulted in environmental imbalances such as global climate change, rising sea levels, and extreme weather. Using annual energy consumption (EC), economic growth (GDP), and carbon dioxide (CO2) emissions in China from 1981 to 2021, this study employed the maximum likelihood estimation method to estimate the parameters of the nonlinear MS-VAR model. Cointegration tests, regimes analysis methods, and impulse response function analysis methods were adopted to explore the differences or similarities in the dynamics of the three under various regimes. The research results are as following. (i) The cointegration test findings demonstrate a long-term equilibrium relationship among EC, economic growth, and CO2 emissions. (ii) Regime analyses exhibit that there are three regimes: "low-level regime," "medium-level regime," and "high-level regime." The three regimes have a mutual transfer transmission mechanism that exhibits nonlinear properties. (iii) Impulse response function analyses show that external EC and GDP shocks favorably impact the other two variables in all three regimes. EC in all three regimes is negatively impacted by external CO2 shocks. Moreover, in the "low-level regime," the relationship between CO2 and GDP has an inverted U-curve, whereas in the other two regimes, the relationship has a negative association. This study can help China formulate reasonable and effective CO2 emissions reduction and energy policies and successfully achieve the emissions reduction goal of the 14th Five Year Plan as well as dual carbon goals. [ABSTRACT FROM AUTHOR]

Identifying the carbon emission characteristics, driving factors, and decoupling status of the industrial subsectors is important for developing effective policy measures. This allows for implementing industrial emission reduction that, eventually, decouple carbon emission and economic growth. Such an analysis is especially important for the case of China on its way towards sustainable development and increasing global interrelationships. However, the literature still lacks comprehensive analysis, especially, at the industry level. This study uses the Logarithmic Mean Divisia Index and decoupling indicator to analyze how different factors contribute to CO2 emissions in 28 industries in China during 2002–2017. The results reveal that the growth of industrial CO2 emissions has been positive but decreasing. The highest CO2 emission change is observed for production and supply of electric and heat power, processing of petroleum, coking, and nuclear fuel, and smelting and pressing of metals. These sectors also show high carbon intensity levels. The economic output (scale) effect and population effect comprise the two major factors promoting the CO2 emission. The energy intensity effect is the key inhibiting factor of the industrial energy-related CO2 emission in China. The suppressive effects of energy and industrial structure have been continuously increasing. The economic growth and CO2 emission has been gradually decoupling in the case of the 28 sectors analyzed. Manufacture of cloths, leather, fur, feather, and related products as well as production and supply of gas exhibit a relatively stable strong decoupling. Based on the decoupling analysis, this study shows that energy intensity has induced the decoupling, whereas the opposite effect has occurred due to economic growth, and the other factors showed little effect on CO2 emission decoupling. [ABSTRACT FROM AUTHOR]

Large amount of carbon emission is the main hazard to environment and human health. The aim of this research is to investigate the impact of economic growth, forest zone, agricultural productivity, and energy consumption on environmental pollution in China using time series data from 1980 to 2020. The underline research utilized dynamic ordinary least‐squares (DOLS) method, Johansen and Engle–Granger cointegration tests, and the autoregressive‐distributed lag (ARDL) technique to analyze the varying data set. To compare findings, fully modified ordinary least squares (FMOLS) and canonical cointegrating regression (CCR) estimators are estimated. Energy use and population raise CO2 emissions with 1% economic development. Long‐term CO2 emissions may be reduced by 1% agriculture production and forestry zone growth. The Granger causality test showed causation between all variables. Results reveal that China might achieve sustainable development goals by cutting down CO2 emissions and mitigate global climate change. The underline research presents policy recommendations for attaining environmental sustainability in China through green investment by reducing carbon emissions. These policies highlight promoting use of renewable energy, financing green technological progression in agricultural productivity, and the ecological feasibility of China's forests. [ABSTRACT FROM AUTHOR]

China faces the challenge of balancing economic development with environmental sustainability as one of the largest economies and the world's top emitter of greenhouse gases. This study investigates the role of fiscal incentives and energy efficiency in fostering green economic growth in China. The Data Envelopment Analysis (DEA) model is used in the analysis, which spans the years 2010 to 2021, to assess the effectiveness of energy use and the influence of financial incentives on environmental sustainability. The results show that increasing energy efficiency reduces environmental deterioration and improves resource utilization, positively contributing to green economic growth. The study also demonstrates the critical role financial incentives, such as tax breaks and subsidies, play in encouraging investments in sustainable practices and clean technology development. These results underline how crucial it is to implement targeted fiscal policies and energy efficiency measures to promote green economic growth in China. [ABSTRACT FROM AUTHOR]

To investigate how to obtain the optimal balance between energy consumption and economic development, this paper proposes a multifactor optimization model (MFOM). Different from previous input–output optimization models, our proposed MFOM comprehensively considers the direct and indirect impacts of sectoral consumption activities on total energy consumption. The results show that MFOM achieves higher energy-saving goals by smaller adjustment to consumption activities than the previous input–output optimization models do. The results also show that the consumption of some products should be limited to achieve the energy-saving and economic growth goals, such as Non-ferrous Metal Ore Mining, Chemical Products and Ferrous Metal Ore Processing. Furthermore, the results indicate that the share of some sectors, especially high-level manufacturing sectors, significantly decreases in the consumption structure after optimization. To maintain the sustainable development of these sectors, the dependence of their production activities on energy-intensive products should be reduced. [ABSTRACT FROM AUTHOR]

China has proposed ambitious goals of carbon peak and carbon neutrality, and will pay more attention to the relationship between economic development and carbon emissions. It's significant to assess the current environmental decoupling and prospect the future conditions in China. This article studies the decoupling status and influencing factors in Chinese provinces from 1996 to 2018 through Tapio decoupling index and decomposition model. The results show that most provinces are currently in a weak decoupling state. The growth of per capita GDP and population will affect the process of strong decoupling, while the optimization of energy intensity, energy structure and industrial structure will promote the realization of strong decoupling. Moreover, this paper prospects the decoupling scenarios of Chinese provinces from 2019 to 2035 and finds that all provinces will achieve strong decoupling before 2040, 2035 and 2030 under different carbon emissions scenarios respectively. To achieve the strong decoupling of economic output and carbon emissions as soon as possible, the government must improve energy efficiency, use renewable energy in large quantities, and promote the industrial transformation and upgrading. [ABSTRACT FROM AUTHOR]

The global economic growth is hindered by resources shortage, energy demand, air pollution and climate. Energy efficiency can reduce some pollutants while potentially increase others. This study refers to sulfur dioxide (SO2), nitrogen oxides (NOx), and dust and smoke (DS) as primary pollutants to distinguish it from secondary ones. The influence of energy efficiency, socioeconomic, and natural climatic factors on air quality is analyzed under the theory of STIRPAT. It is highly coupled between energy efficiency and the spatial distribution of air quality. Increased energy efficiency can improve air quality by reducing SO2 and NOx, but the impact on DS is insignificant. Air pollutants decrease by about 0.531% for every 1% increase in temperature and 0.105% for every 1% increase in precipitation. Consumption will reduce air pollution, and there is an inverted U-shaped relationship between population density, economic scale, urbanization, technology innovation, and air pollution. It is worth mentioning that this work adds temperature and precipitation to the STIRPAT as natural climatic factors, analyzing the impact of energy efficiency on air pollution under the two-factor restrictions of socioeconomic and natural climatic factors. Finally, management suggestions are made to improve air quality. [ABSTRACT FROM AUTHOR]

This study investigates the relationships between energy consumption, urbanization, green finance, and economic growth in China. By utilizing the quantile ARDL model and considering labor and capital as input factors, we analyze the period from 1999 to 2022. Our findings reveal that green finance and urbanization have negative effects on economic growth across different quantiles, in both the short and long run. Conversely, energy consumption exhibits a significantly positive impact on growth in various quantiles. Policymakers are encouraged to implement sustainable energy measures, promote eco-friendly urban planning, and embrace green technology to achieve both economic growth and environmental sustainability. [ABSTRACT FROM AUTHOR]

As the world's largest carbon dioxide emitter, China is curbing coal consumption and increasing natural gas and renewable energy consumption to curb the increase in carbon emissions. At the same time, China is still the largest developing country in the world. Therefore, it is very important to investigate the links between different types of energy consumption, economic growth, and carbon emissions. In this paper, impulse response functions and Granger causality test based on time-varying parameters vector autoregressive model are used to explore the time-varying relationship among CO2 emissions, economic growth, and heterogeneous energy consumption (coal, gas, oil, and renewable energy) in China over the period 1980–2019. The results show that reducing coal and oil consumption and increasing natural gas and renewable energy consumption will not significantly hinder economic growth. In addition, in the long run, reducing coal and oil consumption and increasing renewable energy consumption can significantly reduce carbon emissions. However, after 1998, increasing natural gas consumption will significantly increase carbon emissions. This study reveals the time-varying relationship between heterogeneous energy consumption, economic growth, and carbon emissions, and provides suggestions for China to achieve low-carbon economic growth. [ABSTRACT FROM AUTHOR]

Based on the environmental Kuznets curve (EKC) hypothesis and using Chinese provincial panel data from 2002 to 2019, this study examines how different types of healthcare expenditure and levels of economic development and energy consumption contribute to carbon emissions regionally. Considering the wide regional differences in the development levels of China, this paper uses quantile regressions and draws the following robust conclusions: (1) The EKC hypothesis was validated by all methods in eastern China. (2) The carbon emission reduction of government, private, and social health expenditure is confirmed. Furthermore, the impact of health expenditure on carbon reduction decreases from East to West. (3) Government, private, and social health expenditure all cause reductions in CO2 emissions, with private health expenditure having the largest negative effect on CO2 emissions, followed by government health expenditure and finally social health expenditure. Overall, the limited empirical work available on the impact of different kinds of health expenditure on carbon emission in the existing literature, this study greatly assists policy makers and researchers to understand the importance of health expenditure in improving environmental performance. [ABSTRACT FROM AUTHOR]

In the case of China, there is a need of green energy system to boost growth and environment. However, the current growth of urbanization is putting high pressure on energy system through financial capital. Hence, it is a need to develop such path through renewable energy consumption, capital development, and urbanization to enhance the performance of development and environment. Therefore, this paper contributes to the literature by adding the asymmetries between renewable energy, urbanization, economic growth, and capital investment by covering the period from 1970 to 2021. For this purpose, we apply the nonlinear autoregressive distributed lag model to find the nonlinearities between the variables under study. The findings confirm the asymmetric short- and long-term relationships between the variables. In this sense, capitalization shows the short- and long-term asymmetric impacts on renewable energy consumption. In addition, urbanization and economic growth have long-term asymmetric and positive impacts on renewable energy consumption. At last, this paper provides applicable and practical policy implications for China. [ABSTRACT FROM AUTHOR]

Along with the globalization process, China has achieved high levels of economic growth rates. China, which is among the developing countries, is among the prominent economies in the world with its population and economic potential. Economic growth is among the most important macroeconomic targets in national economies. Sustainability of this target is of great importance. In this respect, green growth has become very important in terms of both sustainable economic growth and economic development. In this study, the relationship between annual financial development, renewable energy and economic integration variables and green growth in the 1990-2019 sample period of the Chinese economy is investigated. Fourier ARDL method was used as empirical method. Empirical findings have shown that there is a long-run relationship. According to both long- and short-term coefficient estimation findings, it has been revealed that financial development has a positive effect on green growth, while renewable energy consumption and economic integration have a negative effect on green growth in China. [ABSTRACT FROM AUTHOR]

Assessing the causal relationships between clean energy consumption and economic growth in China, a central actor in the world's climate future, have received considerable attention among scholars. However, due to the lack of methodological rigour in the causality analysis, available literature failed to provide solid inferences on the links between the variables. Therefore, this study aims to re-examine the variables' dynamic linkages with a more well-established approach from 1965 to 2020. We use a time-varying framework that relaxes the assumption of parameter stability, a remarkable feature that distinguishes our paper from the previous studies. Utilizing the conventional Granger causality test, we fail to detect causation between the variables. However, the evidence of substantial time variation in the causal relationships implies that the standard framework's inference is unreliable. The findings of our time-varying analysis indicate different forms of causality flows in various subperiods. This can be a dependable reason for China to follow its enhanced carbon neutrality target safely. The results of our study also emphasize the significance of considering time-varying causality tests to avoid the risk of misleading inferences. [ABSTRACT FROM AUTHOR]

Poverty alleviation and energy saving are two major issues of sustainable development targets. Meanwhile, financial development (FD) is a powerful engine of economic growth, which is regard as a valid approach to contain the demand for energy consumption (EC). However, few studies link the three factors and explore the specific impact mechanism of poverty alleviation efficiency (PE) on the tie between FD and EC. Thus, we employ the mediation and threshold models to evaluate the influence of FD on the EC in China during 2010–2019 from the perspective of PE. We affirm that FD indirectly promotes EC through the channel of PE. The mediating effect of PE is responsible for 15.75% of the total effect of FD on the EC. Moreover, FD generates a significant threshold impact on the EC considering the change of PE. When the PE exceeds 0.524, the role of FD in promoting EC is strengthened. Ultimately, the outcome suggests policymakers need to prominent the trade-off between energy saving and poverty reduction during the fast evolution of financial system. [ABSTRACT FROM AUTHOR]

This study aims to investigate the impact of ICT capital services on economic growth and energy efficiency in China at both national and industrial levels during the period 2000–2020. To achieve this aim, this study introduces a measurement method for capital services, explores ICT's contributions to economic growth, and analyzes the impact of ICT on energy efficiency. The empirical results of this study indicate that although the ICT capital services scale is relatively small, accounting for only 8.87% of the total in 2020, its growth rate is faster than that of non-ICT capital services, and the distribution of ICT capital services varies widely among different industries. Additionally, based on the economic growth decomposition framework, this study finds that the contribution of ICT capital services to economic growth is 6.95% on average. It is significantly higher in certain industries, such as Financial industry; Information transmission, software and information technology services; Construction; and Manufacturing compared to others. The total factor energy efficiency (TFEE) reveals that industries with higher energy consumption have lower energy efficiency, while the panel regression model illustrates that the development of ICT has a positive impact on improving energy efficiency, with variability across industries. Overall, the findings of this study provide crucial scientific evidence and policy implications for promoting the development of ICT and integrating it with various industries, which can significantly contribute to boosting economic growth and energy efficiency. [ABSTRACT FROM AUTHOR]

The logistics business is a crucial contributor to economic development, yet it is also the leading source of carbon emissions. Economic growth at the expense of environmental deterioration is a challenging issue; this phenomenon offered a new avenue for scholars and policymakers to investigate and address these issues. The recent study is one of the attempts to explore this intricate subject. The goal of this research is to determine whether or not the Chinese logistics sector has an impact on Pakistan's GDP and carbon emissions as a result of CPEC. The research utilized data from 2007Q1 to 2021Q4 using the ARDL approach for an empirical estimate. Due to the mixed order of variable integration and finite data set, the ARDL technique is well deserved, which helps reach sound policy inferences. The study's key results indicated that China's logistic business enhances Pakistan's economic development and carbon emissions in the short and long term. Similarly, China's energy usage, technology, and transportation contribute to Pakistan's economic progress at the price of environmental damage. The empirical study may be a model for other developing nations, given Pakistan's viewpoint. With the support of the empirical results, policymakers in Pakistan and other associated countries would be able to plan for sustainable growth in conjunction with CPEC. [ABSTRACT FROM AUTHOR]

Our paper investigates the association of renewable energy, financial development, urbanization, and growth in China along with technology. The newly developed econometric techniques (asymmetries) have been applied to explore short and long-run nonlinear relation among variables by utilizing annual data for the period of 1965–2021. In nonlinear cointegration, findings highlight the importance of renewable energy consumption for growth and development. Urbanization also confirms a positive association with growth and development where positive shocks were more dominant to support the growth process. The stock of technology brings a positive impact on growth and development whereas financial development results reveal to consider policy carefully. Asymmetric causality supports a uni-directional causal association between renewable energy, financial development, and growth. Policy recommendations are also highlighted according to the results. [ABSTRACT FROM AUTHOR]

This paper investigates the role of export quality in climate action goal of the sustainable development goals in emerging Asian countries. For this purpose, the empirical model that observes the impact of real GDP, energy use and export quality index on carbon emissions is constructed and is analyzed by ARDL bounds testing approach for the period from 1970 to 2014. We also include the square of real GDP as independent variable to observe the existence of environmental Kuznets curve (EKC) hypothesis which implies the parabolic relationship between economic growth and environmental degradation. The findings show that increase in export quality leads to a fall in CO2 emissions for China and India. In contrast, the effect of increasing export quality increases CO2 emissions in Thailand and the Philippines. Lastly, our asymmetric causality results show that the positive shocks of export quality causes positive shocks of CO2 emissions in Thailand and Indonesia. Furthermore, we found that positive export quality shocks cause negative CO2 emissions shocks in India while negative export quality shocks cause positive CO2 emissions shocks in China. We also confirm the inverted U-shaped EKC hypothesis in China and Thailand. [ABSTRACT FROM AUTHOR]

Building a sustainable energy system and achieving sustainable economic growth has always been China's development goal. However, under the promotion incentive and information asymmetry, local governments may choose to sacrifice the ecological environment to maintain expected economic growth goals. This paper analyzes the relationship between economic growth targets and green energy efficiency (GEE) by using panel data models and spatial econometric techniques. Moreover, the mediation effect model and threshold effect model are used to study their influence mechanism and the possible nonlinear relationship. The results indicate that economic growth targets reduce the efficiency of GEE. The impact of environmental regulation on GEE is "U" shaped. Environmental regulation plays a positive moderation role between economic growth targets and GEE. Additionally, higher levels of technological innovation, industrial upgrading, and environmental regulation result in a reduction in the negative effects of economic growth targets on the GEE. However, the improvement in the foreign direct investment can increase the negative influences of economic growth targets on the GEE. [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]

This paper studies the impact of financial inclusion on energy consumption in China since the new millennium by using provincial data in China from 2000 to 2019. A financial inclusion index is first constructed, and the spatial-temporal evolution of China's financial inclusion and energy consumption are explored. Second, a spatial econometric model is applied to investing their relationship. Third, the mechanism on how financial inclusion may affect energy consumption is investigated through the mediation effect model. Results show that both financial inclusion and energy consumption show signs of polarization in China. Besides, most provinces saw a significant increase in their per capita energy consumption. Further, the relationship between financial inclusion and energy is U-shaped. Lastly, economic growth and technology upgrading mediate the impact of financial inclusion on energy consumption, with the direct effects (II) dominating the mediation effects. Some policy suggestions are also given. [ABSTRACT FROM AUTHOR]

This research aims to utilize quarterly global VAR data from April 1, 2020, to September 30, 2021, to assess the influence of the economic recovery of China following the COVID-19 outbreak on global economies. China is one of the first big economies globally to show indications of recovery following the COVID-19 pandemic. The nation's economic growth has the biggest long-term influence on middle-income nations (0.17%) followed by low- and middle-income economies (0.16%) and high-income economies (0.16%) (0.15%). The chain reaction of China's economic growth is most visible in high-income nations (0.11–0.45%), followed by middle-income countries (0.08–0.33%) and low-income countries (0.02–0.05%). Our findings show that the post-COVID-19 economic rebound in China will mostly benefit middle-income nations, with low- and middle-income countries following closely after. After COVID-19, the influence of the economic recovery of China is most visible in the rise of energy consumption in high-income nations, followed by middle-income economies. It is also worth noting that the influence of China's economic expansion on low- and middle-income economies does not always imply a rise in energy consumption. Overall, China's economic recovery has a significantly stronger influence on other countries' economic development than other countries' energy consumption has on other economies' growth. [ABSTRACT FROM AUTHOR]

As China reaffirms its commitments to limit the climate change risk and improve air quality, a combination of new policy and technology opportunities is presenting itself. A national emission trading scheme (ETS) begun in 2017 and is showing great promise, creating decentralized incentives for cost effective pollution mitigation. At the same time, sustained energy sector innovation is driving the costs of renewable electric power generation below those of fossil fuel substitutes. Early economic evidence of ETS measured pollution reductions, but has not addressed important economy-wide net benefits. This paper focuses on technology and energy cost savings and is the first to account for three multiplier effects—shifting consumption patterns, job growth, and the benefits of induced productivity growth—that would result from accelerated renewable electricity deployment in China. Results from a dynamic recursive computable general equilibrium model for 2017 to 2030 show that expanding renewable deployment can interact with the ETS to slash GHG emissions, as well as energy costs, stimulating significant long-term economic growth. These results suggest that China should accelerate its clean energy transition, not only for the air-quality and climate benefits, but to fulfill the energy sector's potential to promote innovation, employment, and economic growth. [ABSTRACT FROM AUTHOR]

Reducing exhaust emissions, promoting economic development, and realizing clean energy utilization have always been concerns in China. To measure the relationship between them, this study selects the data related to energy consumption, economic growth, and exhaust emissions from 2000 to 2019 in 30 Chinese provinces. By constructing a panel vector autoregressive (PVAR) model, the dynamic relationship between them in China is quantitatively analyzed. The results show that there is a long-term interaction between energy consumption, economic growth, and exhaust emissions. Among them, economic growth is highly dependent on energy consumption, but it can promote the reduction of exhaust emissions. However, energy consumption will produce a large amount of industrial waste, such as sulfur dioxide and carbon dioxide emissions. Specifically, the industrial structure and energy structure have the most obvious impact on reducing industrial sulfur dioxide emissions and carbon emissions, with the proportion between 0.071–0.090 and 0.031–0.032, respectively. Therefore, the adjustment of industrial structure and energy structure is the key to exhaust emission reduction. [ABSTRACT FROM AUTHOR]

The strategic formulation of economic growth targets (TAR) plays an essential role in economic development, but it may also affect energy consumption. Using China's provincial data from 2000 to 2018, this study empirically analyzes the impact of TAR on energy consumption. The results show that the local TAR significantly increases energy consumption, and this effect is significant in the eastern and midwestern regions, but there are differences in different development stages. Meanwhile, the unreasonable industrial structure and extensive urbanization mode are the important influencing mechanisms that TAR affects energy consumption. More importantly, Chinese-style fiscal decentralization is an important factor in explaining the relationship between TAR and energy consumption. As the degree of fiscal decentralization increases, the promotion effect of TAR on energy consumption becomes more obvious. In conclusion, the theoretical and empirical evidence of this study indicates that deepening the reform of government target-based management system is helpful to stimulate the motivation of local governments in energy conservation. [ABSTRACT FROM AUTHOR]

Since the debate concerning economic growth, energy consumption, and environmental degradation is a burning issue in the last few decades. Yet the outcomes are controversial and requires more empirical work. This study used novel research methods to investigate the said issue in case of China since is the leading energy importing and pollution emitting economy. The time series data covers the period from 1969 to 2018 is analyzed via employing the novel Quantile-on-Quantile regression methods. The estimated results unveil that fossil fuel consumption significantly enhances carbon emissions in the country in the lower and middle quantiles. Besides, the economic growth showed an inverted U-shaped impact on the carbon emissions, where the lower-medium quantiles showed positive and the upper quantiles exhibit negative impact on carbon emissions. Besides, the positive association between economic growth and fossil fuel emissions are also evident in the analysis. The Granger causality indicates that there is a bidirectional causality between the study variables – validating that economic growth and fossil fuel consumption are the primary sources of increased emissions level. On the basis of empirical results, this study suggests the adoption of energy efficient/saving products and services, diverting economic growth to renewable and environmentally friendly energy resources, technological innovation and increased investment in the research and development to reduce dependency on fossil fuel energy consumption and attain low carbon economy. [ABSTRACT FROM AUTHOR]

Since the last few decades, scholars and policy-makers have been struggling to find ways to achieve carbon neutrality target or a low carbon economy. To contribute to the existing literature regarding the said issue, this study aims to investigate whether energy efficiency could lead to achieving carbon neutrality target in the case of China. Also, this study analyses the association of economic growth to energy-related greenhouse gas emissions while using quarterly data over the period from 1990Q1 to 2014Q2. Empirical findings of the study suggest the mixed order of integration and Cointegration between economic growth, energy efficiency, and energy-related greenhouse gas emissions. This study employed a Quantile-on-Quantile regression approach to examine the long-run association at various quantiles. The estimated results asserted that energy efficiency holds a weaker relationship in the lower and medium quantiles, while relatively higher association to energy-related emission in the upper quantiles. On the other hand, economic growth and its squared are found significantly and highly associated with enhancing energy-related emissions in the country. Besides, the frequency domain causality indicates a causal association running from energy efficiency and economic growth to energy-related greenhouse gas emissions. This study recommends revised policies for energy efficiency and suggests that economic growth could be used as a remedial measure for environmental recovery by enhancing investment in the renewable energy sector, energy efficiency, and structural transformation of the industrial sector. [ABSTRACT FROM AUTHOR]

China's extensive economic growth has been accompanied with high levels of pollution, and excessive energy consumption has brought serious pollution problems. The use of financial resources to regulate green production modes and encourage high‐quality economic development has become a major focus in academia. At the same time, growth enterprise market (GEM) enterprises, which mainly operate in technology‐intensive industries, are assumed to have a simulating effect on regional innovation. Therefore, this paper utilizes the capital return differences of 4437 listed companies and 920 GEM companies based in 30 provinces of China from 2008 to 2018 to quantitatively analyze the levels of financial misallocation. With two‐stage regression method, the direct effect of financial misallocation on regional green total factor energy efficiency (GTFEE) and the indirect impact observed when taking regional innovation as an intermediary variable are discussed. Furthermore, dynamic threshold panel regression and heterogeneity analysis are used to verify the above nonlinear relationship. The empirical findings indicate that financial misallocation enhances innovation capability and further restrains GTFEE. With an improved degree of marketization and environmental regulation, the inhibitory effect of financial misallocation on GTFEE is more significant. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to reveal the mechanism and process of the dynamic evolution of the economy-energy-environment (EEE) system and study the variables that determine the speed of system evolution and development. The innovation is to overcome the defect of single index by constructing a system evaluation index and reveal the regional EEE system's evolution mechanism based on Haken's synergetic theory to supplement a systematic perspective's empirical evidence. It selects 30 provinces, municipalities, and autonomous regions in China to empirically analyse the evolution mechanism of the EEE system from 2005 to 2019. The empirical results show that economic development is the order parameter of the evolution and development of the EEE system. In the process of system evolution, the economic development subsystem is the decisive factor in EEE system evolution. In terms of the positive feedback mechanism of order parameter combination, the EEE system forms a positive feedback mechanism for increasing economic development in the stage of evolution and development. The negative feedback mechanism of decreasing environmental pollution emissions is formed in the EEE system. The increase in pollutant emissions has a certain inhibitory effect on economic growth. The improvement in the economic development level has no promoting effect on pollutants, and economic development, in turn, reduces environmental pollution. [ABSTRACT FROM AUTHOR]

Since the Industrial Revolution, fossil fuels have become the main energy source for economic development. However, fossil fuels have also been linked to serious environmental impacts. China has recently undergone rapid economic growth, but its development model demands large amounts of energy and causes severe pollution. Therefore, there has been a recent shift toward the development of coordinated strategies to achieve economic growth while minimizing energy consumption and preserving the environment. This study sought to explore the spatiotemporal evolution of the coordination degree between economic growth, energy consumption, and environmental conservation (i.e., the "3E" system) in China, thus establishing a basis to improve coordinated development and minimize regional differences. This study evaluated 30 Chinese provinces using mathematical models. Between 2000 and 2019, the coordinated development level of the components of the 3E system in China increased steadily but remained generally low. Clear spatial agglomeration was also identified at the provincial scale, with the highest values occurring on the east coast and lower values occurring in the west and middle provinces. [ABSTRACT FROM AUTHOR]

The rapid development of digital finance has delivered significant benefits, such as sustainable development and economic growth. We explore the relationship between digital finance and green total factor energy efficiency (GTFEE) for the first time, filling a gap in the existing literature. This paper uses dynamic panel models to explore digital finance's impact on GTFEE at the Chinese city-level panel data from 2011 to 2018. The results show that digital finance can significantly improve urban GTFEE, and the findings remain robust with various tests. Second, the mechanism analysis indicates that digital finance can improve GTFEE by promoting urban green technology innovation and industrial structure upgrading. Further study shows that digital finance has a better effect on the improvement of GTFEE in central and western cities, small cities and non-resource-based cities, but has no significant or small impact on GTFEE in eastern cities, large cities and resource-based cities, reflecting the inclusiveness of digital finance. [ABSTRACT FROM AUTHOR]

While promoting the economic growth, energy has also brought pollution problems to the world environment, which has gradually become a bottleneck impeding sustainable economic development. In view of the rapid evolution of urbanization and industrialization, economic growth is increasingly dependent on the energy consumption, the development of the two is difficult to coordinate, and the internal contradictions are becoming increasingly serious, which hinders the sustainable development of economic growth. This study establishes the relationship between energy consumption and economic growth according to the energy Kuznets curve and studies the future trend of China's sustainable development through the comparative analysis of the energy Kuznets curve of the United States and Germany. The results show that, at the turning point of energy consumption, China's energy economic rate is higher than that of Germany and the United States. In addition, in terms of urbanization rate and industrial structure, although China's tertiary industry has made a breakthrough, it is still lower than that of the United States and Germany, but the level of urbanization rate has made significant progress. In short, China has obvious advantages in future economic development and has a late developing advantage compared with the United States and Germany. This paper makes an empirical analysis of the relationship between energy consumption and economic growth in OECD countries and finds out the turning point of energy consumption, so as to provide a theoretical basis for coordinating China's energy consumption and economic growth. [ABSTRACT FROM AUTHOR]

With rapid economic growth, energy consumption and emission reduction have become one of the most urgent issues in the Yangtze River Delta region(YRD), China's first important economic circle. In this paper, we estimate the energy-related CO2 emissions in the YRD during 2005-2016 using the emission measurement method provided by the IPCC (2006). In addition, the effects of various driving factors, such as population size, economic scale, industrial structure, energy intensity and energy structure, on CO2 emissions in this region are quantitatively analyzed by applying the LMDI factor decomposition model. The results show that the primary influencing factors of CO2 emissions in the YRD are economic growth and energy intensity. Population size and economic growth promoted CO2 emissions during 2005-2016, and economic growth is the decisive driving factor. On the contrary, the industrial structure, energy intensity, and energy structure of the YRD have inhibitory effects, and energy intensity is the dominant factor among them to restrain the growth of CO2 emissions. Besides, we discuss these results in detail and find that industrial structure and energy structure have great potential for CO2 emission reduction in the YRD. Finally, we put forward corresponding sustainable policy suggestions for optimizing industrial structure and energy structure to promote low-carbon economic development. [ABSTRACT FROM AUTHOR]

With less than ten years left to meet its pledge to peak carbon dioxide emissions (peak emissions hereafter) by 2030, China has entered a critical emissions reduction stage. How to meet this commitment in a context in which GDP per capita will double from 2020 by 2035 is a major decision-making issue for the Chinese government and people and one which warrants further study. To reveal the relationships between the GDP growth rate, the rate of decrease of carbon intensity and the time to reach peak emissions, this study translates the question as to "when China's carbon emissions peak will occur" into "how can one control the rate of carbon intensity decrease at a given GDP growth rate". In the light of the results of a random forest algorithm used to identify and project the key drivers of carbon intensity in China, a mathematical model was developed to simulate different scenarios relating to decreases in carbon intensity. The date at which Chinese carbon emissions will peak is predicted by comparing the rate of decrease of carbon intensity with the GDP growth rate. The results show that the time to peak emissions depends on the relationship between the rate of decrease of carbon intensity and the GDP growth rate, where the former depends mainly on the energy structure and policy. If China's annual GDP growth rate were 5.0% during the 15th Five-Year Plan, and if the share of non-fossil energy in total energy consumption were 23.0% or above, China's carbon emissions will peak before 2030. If the share of non-fossil fuels were 20.0% or less, China might not be able to reach its 2030 target. In this latter case an acceleration in the pace of energy restructuring would be required to reach peak emissions before 2030. The projected peak emissions scenarios suggest that the carbon peak will occur between 2025 to 2029, with average peak emissions of 11.2 billion tons and a distribution ranging from a minimum of 10.5 billion and a maximum of 11.9 billion tons. If the GDP growth rate were 4.5%, 5.5% or 6.0% during the 15th Five-year Plan, the share of non-fossil energy must reach 23.0%, 25.0% or 27.0%, respectively, to ensure that emissions peak by 2030. The results of this study provide a series of reference points for China's pursuit of feasible pathways to peak carbon emissions by 2030. [ABSTRACT FROM AUTHOR]

In the extant literature, there are numerous discussions on China's environmental sustainability. However, few scholars have considered renewable energy consumption and trade policy simultaneously to debate environmental sustainability. Therefore, this paper attempts to examine how renewable and non-renewable energy consumption, bio-capacity, economic growth, and trade policy dynamically affect the ecological footprint (a proxy for environmental sustainability). Using the data from 1971 to 2017 and employing the auto-regressive distributed lag model to perform an empirical analysis, the results demonstrate that renewable energy consumption and trade policy are conducive to environmental sustainability because of their negative impacts on the ecological footprint. However, the results also indicate that bio-capacity, non-renewable energy consumption, and economic growth are putting increasing pressure on environmental sustainability due to their positive impacts on the ecological footprint. Moreover, to determine the direction of causality between the highlighted variables, the Yoda-Yamamoto causality test was conducted. The results suggest a two-way causal relationship between renewable energy consumption and ecological footprint, non-renewable energy consumption and ecological footprint, and economic growth and ecological footprint. Conversely, the results also suggest a one-way causal relationship running from bio-capacity and trade policy to the ecological footprint. [ABSTRACT FROM AUTHOR]

China's coastal region is the major geographical unit for the future development of China's industrial sector. The transformation of basic structure to high-class development in China's coastal places is a significant tool for promoting the changes related to quality, power and efficiency in regional economic development. In the 21st century, environmental and energy issues have increased worldwide, and challenges related to environmental pollution, energy crises, and ecological imbalances have emerged. To climate change and energy utilization, the sustainable progress of clean energy is the new route of future energy development. Based on China's non-polluting energy growth process in the last ten years, this article explores China's clean/green energy policies and economic growth development plans. Clean energy utilization is crucial for sustainable development in the context of high-quality economic growth and climate change. However, the monetary evolution and carbon emission are not investigated whole from the clean energy aspects. Using Wind energy sources as the acceptable variable, this paper employs threshold regression and impulse functions to assess the energy consumption and economic growth on carbon emission in 30 Chinese provinces over the 2000 to 2020 period. The Deep Belief Network (DBN) model predicts wind energy utilization and efficiency. The results show that economic development and carbon emissions are connected. Further, growth influences promote the offset of carbon emissions. Green innovation alters the nexus of carbon emissions, and China's economy reduces carbon usage. It provides the decision-making policies for clean energy development. • China's Coastal region is the major geographical unit for the future development of China's industrial. • In high-quality economic growth and climate change, clean energy use is vital for sustainable development. • The utilization of wind energy and it's efficiency is predicted using Deep Belief Network (DBN) model. • Empirical results link economic growth with carbon emissions, showing growth promotes emissions offset. • Green innovation changes the economic growth-carbon link, aiding China's carbon reduction efforts. [ABSTRACT FROM AUTHOR]

This study examines to what extent foreign private investment (FPI) affects the clean industrial environment and sustainable economic growth through developed countries investment in China. Moreover, this study investigates an association among FPI, CO2 emission, energy consumption, trade openness, and sustainable economic growth. This study uses random effects and generalized least squares (GLS) and panel VAR estimators for data analysis. The results show that China's economy has a great positive impact on the location and choice of investment in domestic markets in emerging countries and developed countries. In addition, investment in emerging and developed economies has increased the contribution of domestic enterprises and environmental sustainability to the national economy. The further results show that foreign private investment and gross domestic investment have positive impact on sustainable economic growth. [ABSTRACT FROM AUTHOR]

The study tests the EKC hypothesis, forecasts future paths, and models the dynamic relationship between ecological and economic variables in China. The problem of sustainable and green growth in China arises with the rebirth of the Belt and Road Initiative (BRI) program. Although there has been various research on the subject, the basic EKC model results are often conflicting. To obtain consistent parameter estimates, the basic EKC model was extended; the study's contributions or novelties include avoiding the omitted variable bias by introducing urbanisation rate and international trade, which according to the literature, simultaneously influence pollution levels significantly. Also, more recent and robust estimation techniques including the Fourier ADF (FADF) unit root test, the time-varying bootstrap causality test, the Fourier ADL and Gregory-Hansen cointegration tests, fully modified ordinary least squares (FMOLS), vector error correction model (VECM), and the forecast error variance decomposition (FEVD) analysis were employed. The techniques mentioned earlier were confirmed using traditional methods such as the Johansen cointegration test and the traditional testing methods for unit root. The EKC is not valid in China. Cointegration and long-run relationships are established. Also, the future path of CO2 emissions continues to be on the rise. While economic growth, energy consumption and trade significantly increase CO2 emissions, urbanisation significantly lessens pollution from CO2 emissions in the long run. Policy recommendations include using new technologies, energy diversification, and the ultimate switch to clean energy use, including hydropower, wind power, solar energy, bio-energy, and tidal energy. Also, the need for increased urbanisation in China is critical to reducing CO2 emissions. It is partly because urban agglomeration allows for the same output to be produced using fewer resources. [ABSTRACT FROM AUTHOR]

The present research purposes to investigate the derivers of ecological footprint in China by explaining the "environmental Kuznets curve". It examines the short-term and long-term effect of non-renewable energy consumption, CO2 emission, and economic growth (GDP) on ecological footprint in China. To achieve this purpose, the current study uses secondary data of 36 years for China and applies time series "auto-regressive distributed lag" modeling to assess short range and long-range effects. Findings of the current study reveal that the CO2 emission significantly positively derives the ecological footprint in long run while the economic growth significantly negatively derives the ecological footprint in long run. It is further found that the CO2 emission significantly positively derives the ecological footprint in short run while the economic growth significantly negatively affects the ecological footprint in short run. It means that the CO2 emission is a positive short-range as well as long-range deriver of ecological footprint while the economic growth is a negative short-term and long-range predictor of ecological footprint in China. However, the non-renewable energy consumption has not been supported as the significant deriver of ecological footprint, neither in short range nor in long range. The current study has strong implications because it will help Chinese policymakers to control environmental degradation and China's ecological footprint through better polices. [ABSTRACT FROM AUTHOR]

As the world's largest energy consuming country, it is important to study the mechanisms of improving renewable energy and energy efficiency to achieve green economic growth in China and globally. Therefore, this study investigates the impact of environmental regulations on green economic growth and renewable energy development in China, respectively. First, this study measures the level of green economic growth in Chinese cities by the Metafrontier-Global-SBM super-efficient data envelopment analysis (DEA) model from the perspective of energy efficiency. And the environmental regulation intensity was measured using an improved fuzzy comprehensive evaluation method. Second, a spatial econometric model based on longitudinal data was constructed to examine the non-linear effects of environmental regulations on green economic growth and its spatial spillover and feedback effects. The results indicated a U-shaped non-linear effect of energy efficiency-related environmental regulation on green economic growth as well as a spatial spillover effect and spatial feedback effect. Finally, the impact of environmental regulation on renewable energy development was investigated. The results show that renewable energy development, an important component of green economic growth, is equally dependent on the implementation of environmental regulation policies and that environmental regulation makes a significant contribution to renewable energy development. The findings of this paper provide a basis for the realization of green economic growth and the formulation of renewable energy policies in China. • Impact of environmental regulation on renewable energy development was investigated. • A spatial econometric model of 286 Chinese cities from 2003 to 2018 was constructed. • Environmental regulation has a significant U-shaped effect on green economic growth. • Non-linear effects include spatial spillover and spatial feedback effects. • Environmental regulation promotes green growth earlier in resource-based cities. [ABSTRACT FROM AUTHOR]