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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]

The renewable energy+energy storage model has an important role to play in achieving China's proposal of the carbon peaking and carbon neutrality goal. In order to study the development mechanism of renewable energy+storage cooperation with government participation, this paper constructs a three-party evolutionary game model among government, renewable energy generators, and energy storage service suppliers, based on the data of a renewable energy+storage project in a Chinese province. In this paper, we analyze the game process and the factors affecting the behavioral strategies of the three parties through numerical simulation. The study shows that the government regulation has a positive effect on the cooperative development of renewable energy+energy storage, and it can effectively restrain the wasteful phenomenon of renewable energy generation by means of punishment and improve the operating income of cooperative projects by means of subsidies, which can help the enterprises to broaden the application scenarios of energy storage. The government can effectively promote the improvement of renewable energy+energy storage cooperation mechanism by formulating regulatory mechanism, controlling the cost of supervision, and dynamically adjusting the intensity of supervision. Therefore, the research in this paper not only enriches the research related to renewable energy+energy storage mode but also provides valuable reference for the government to formulate regulatory policies related to renewable energy+energy storage. [ABSTRACT FROM AUTHOR]

In recent years, excessive emissions of carbon dioxide have further intensified global warming, which poses a great threat to human society. The best way to reverse this situation is to take action to equalize the "carbon emissions" with the "carbon absorption," i.e., carbon neutrality (CN). To better understand the evolution and display a broad panorama of CN research, this paper provides a comprehensive bibliometric analysis of publications in the field of CN from 2006 to 2021. We use the Web of Science Core Collection as the data source, and a total of 633 publications have been retrieved. In the paper, we measure the productivity and influence of publications through recognized bibliometric metrics, and visually analyze publications using VOS Viewer and CiteSpace. The analysis results show that China is the most productive country/region. The study illustrates that in order to reach the goal of CN, it is necessary to reduce carbon emissions such as full using renewable energy. Simultaneously, it is also essential to enhance the "negative emissions" of carbon such as taking advantage of carbon sink and carbon capture, utilization, and storage. This paper provides some references for scholars who are interested or research in this field. [ABSTRACT FROM AUTHOR]

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

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

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

From a spatial perspective, this paper constructs a spatial Durbin model based on the adjacent weight matrix to analyze the impact of environmental regulation on the development of renewable energy in 30 provinces (autonomous regions and municipalities directly under the Central Government) in China from 2007 to 2020. The results show that (1) both environmental regulation and renewable energy development have positive spatial autocorrelation and form relatively similar spatial agglomeration areas, specifically showing the characteristics of "high-high" agglomeration in resource-rich areas and "low-low" agglomeration in resource-scarce areas. (2) Environmental regulation significantly promotes the development of local renewable energy and has a significant spatial spillover effect on the development of renewable energy in neighboring provinces. (3) The moderating effect results show that renewable energy installed capacity and electricity demand play an inverse moderating role between environmental regulation and renewable energy development. (4) From the perspective of different regions, the impact of environmental regulation on the development of renewable energy is heterogeneous. Based on the research conclusions, this paper finally provides corresponding policy suggestions from three aspects: regional cooperation, technical support, and differentiation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to determine the spatial spillover effects of renewable energy on carbon emissions in China's less-developed areas. However, few studies have considered this issue from the perspective of less-developed areas. Based on panel data of 21 provinces in China from 2000 to 2017, this paper analyzes the spatial spillover effects of renewable energy on carbon emissions using Moran's I and Spatial Durbin Model (SDM). The results suggest that, first, Moran's I ranges from 0.378 to 0.519, Moran scatter plot presents that provinces are located in the high–high (HH) and low-low (LL) quadrants, indicating provincial carbon emissions in the study area have a significant spatial correlation and agglomeration. Second, under the three matrices, the direct effect coefficients of renewable energy are -0.2522, -0.2639 and -0.2601, this shows that renewable energy is beneficial to local carbon emissions reduction. In contrast, the indirect effect coefficients of renewable energy are 0.0605, 0.1012 and 0.1125, which means higher renewable energy consumption in a single area is conducive to the improvement of carbon emissions to neighbouring areas. Third, urbanization, industrialization, physical capital and other variables have different impacts on local and nearby carbon emissions. This study provides empirical evidence to achieve carbon emission reduction targets by government policymakers. [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]

As a financial innovation model to promote sustainable economic development, carbon finance promotes green and inclusive economic development by reshaping the financial system. As a big energy consumer, China has been committed to the green transformation of energy structure, and carbon finance has been regarded as an important tool to support carbon emission reduction. This paper divides carbon finance from three levels, financial macro, environmental governance, and technological development, and selects 17 indexes to measure the development level of carbon finance in China. Time series regression model and the entropy weight method (EWM) are used to analyze the impact of carbon finance on China's energy consumption structure. The empirical results show that carbon finance plays a positive role in promoting China's energy consumption structure, and developing carbon finance is conducive to the use of clean energy and the optimization of energy consumption structure in China; carbon finance can further optimize China's energy consumption structure by investing capital, resources, and technology in industries related to promoting clean energy consumption. Therefore, China should continue to develop carbon finance and promote the establishment of a unified national carbon trading market; at the same time, China should use the CCER trading mechanism to promote the development of renewable energy and enhance the endogenous driving force of energy transformation by promoting technological progress. [ABSTRACT FROM AUTHOR]

Renewable energy consumption has a strong impetus in promoting energy conservation and emission reduction, which is a new path leading to clean and low-carbon development. Based on that, this paper uses the data of carbon productivity, renewable energy power consumption level, technological progress, national economic development level, population, energy efficiency, industrial structure rationality, and other data in 30 provinces in China from 2011 to 2020, based on the STIRPAT model, conducts an empirical analysis on the impact of renewable energy power consumption on carbon productivity in Chinese provinces while considering both the spatial horizontal dimension and the temporal vertical dimension. The empirical results show that (1) Chinese carbon productivity presents an obvious spatial spillover effect and presents the spatial positive correlation distribution characteristics of "high-high" type agglomeration and "low-low" type agglomeration. (2) The utilization of renewable energy plays a positive role in promoting the development of low-carbon economy. The perspective of the horizontal spatial dimension shows a positive spatial spillover effect. The perspective of the longitudinal time dimension shows a marginal increase in the overall improvement of the environment. (3) Among the seven regions in China, the consumption of renewable energy in North China, East China, and Central China brings a dominant effect on carbon productivity. (4) About 29% of the positive effect of renewable energy consumption on carbon productivity is indirectly realized by technological progress. Finally, the article puts forward targeted policy suggestions. [ABSTRACT FROM AUTHOR]

Renewable energy plays a significant role in achieving energy savings and emission reduction. As a sustainable and environmental friendly renewable energy power technology, concentrated solar power (CSP) integrates power generation and energy storage to ensure the smooth operation of the power system. However, the cost of CSP is an obstacle hampering the commercialization of this emerging industry, so the paper studies the technical characteristics, economic analysis, and policy implications of CSP. This paper sorts out the relevant policies of CSP and uses the levelized cost of electricity (LCOE) model by considering financial parameters, investment parameters, operation and maintenance parameters, tax parameters, capacity parameters, etc., to analyze the economics of CSP. The model parameters are set by the actual situation of CSP projects. The economic evaluation of different technology types of parabolic trough (PT), solar tower (ST), secondary reflection ST, and linear Fresnel reflector (LFR) is carried out. The LCOE of PT project is 1.11 RMB/kWh (0.17 US$/kWh), the ST project is 0.93 RMB/kWh (0.14 US$/kWh), the secondary reflection ST project is 0.97 RMB/kWh (0.15 US$/kWh), and the LFR project is 0.92 RMB/kWh (0.14 US$/kWh). The results show that the grid parity era of CSP in China is within reach, and ST is the most potential technology type. Based on the results of economic analysis and the problems faced by CSP in China, this paper puts forward policy implications by preferential loans, tax incentives, and R&D fund support to promote the development of CSP. [ABSTRACT FROM AUTHOR]

China states to build new power system dominated by new energy power to promote the targets for peaking carbon emissions by 2030 and achieve carbon neutrality by 2060. Peaking regulation ancillary services provided by coal-fired power units is an essential solution to mitigate the volatility and instability of large-scale renewable energy for China's specific power mix. However, when the coal-fired power units operate at a low power output, the intensity of both coal consumption and carbon emissions gradually rises with the falling output rate. Moreover, cutting down the power output of coal-fired units frequently will damage the technical life. Given the impacts of power market reform and carbon mitigation targets, whether to participate in the energy market or the peaking regulation ancillary service market is an urgent issue for coal-fired power units. Considering the discrepancy in costs and benefits of various units at different output rate, this paper proposes a multi-objective optimization model to solve the issue from the perspective of the coal-fired power generators, in which both economic profit and carbon reduction goals are coordinated. Sequential quadratic programming is adopted to solve the nonlinear optimization problem. In order to study the difference in the decisions made by varied technical units, 7 different types of units are analyzed in the case study. The scenarios analysis indicates that large-capacity and new coal-fired power units are better to participate in energy market since it can give full play to the advantage of higher generation efficiency, while the small-capacity ones are suitable to provide flexible service in the peaking regulation ancillary service market. Besides, simple low-carbon objective will burden the cost of coal-fired power units and challenge the sustainable transition of power system. Hence, the power system should balance both economic profit of generators and national carbon mitigation targets during the low-carbon transition. [ABSTRACT FROM AUTHOR]

In 2020, China pledged to peak its carbon emission before 2030 and achieve carbon neutrality before 2060. These ambitious carbon targets will inevitably boost the development of renewable energy generation, which has advantages from energy and water perspectives but disadvantages from land use perspective. Therefore, it is necessary to discuss the interaction among renewable energy development, water consumption as well as land use in the power sector, and determine a reasonable power-related land use range for the land administration in China. In this research, a series of multi-period, multi-regional power system optimization models with different objective functions and constraints are established to study the interrelationship among renewable energy development, water consumption, and land use in the coverage area of China Southern Power Grid from 2018 to 2030, and provide a reasonable land use range for the power sector in this region in 2030. Based on the above calculation results, the development of renewable energy promoted by energy and water policies will increase the land use of power sector under a cost objective function, and the minimum land area demand for this power system in 2030 considering energy and water policies is 24785.14 km2. What is more, according to the influence of land use constraint on the total cost of power sector from 2018 to 2030, this paper selected the increase ratio from 5 to 16% compared with the minimum land area demand as the reasonable land use range. [ABSTRACT FROM AUTHOR]

Since the start of twenty-first century, the globe has bumped into several crises, such as the sudden rise of oil prices in 2003 and the large-scale global financial crisis in 2007–2008. However, the most recent COVID-19 outbreak has slowed fiscal progress and initiated instability in the prices of commodities-based natural resources. The instability of prices of natural resources attracted the focus of academicians and policymakers. Moreover, the recent pandemic also pushed up the need of green finance and renewable energy investment for renewable energy development. The current study, thus, explores sustainable economic advancements via natural resource rents, green financing, renewable electricity energy, and investment in renewable energy projects in China over the period of 2000 to 2023 including years of pre-post COVID-pandemic. The current paper used CCR (canonical cointegrating regression), DOLS (dynamic ordinary least squares), and FMOLS (fully modified ordinary least squares), for its empirical investigation. The results demonstrate the cointegration of first-differenced stationary variables in the longer run. The parameter of natural resource rents shows that the volatility of natural resource prices adversely influences the sustainable economic advancement of China. Findings also demonstrate that green finance strategy can simultaneously control the high-emission situation and increase economic development of country. Additionally, the findings reveal the positive effects of renewable electricity energy output, and investment in renewable energy projects for sustainable economic advancements. [ABSTRACT FROM AUTHOR]

This paper empirically investigates the effects of the green credit policy (GCP) on the total amount, quality, and quantity of green innovation in renewable energy enterprises (REEs) by employing the difference-in-differences (DID) model. Analyses examining the channel, moderating, and economic effects are conducted using a sample of Chinese listed companies between 2008 and 2021. The results indicate that the GCP significantly promotes the total amount, quality, and quantity of green innovation in REEs. This impact on REEs is mainly through a reduction in green agency costs and an increase in research and development (R&D) spending. In addition, the promotional effects are more predominant in firms subjected to intensified environmental enforcement and benefiting from increased governmental subsidies. Moreover, this positive impact is particularly evident in regions with less environmental pollution and lower economic development. Overall, the adoption of green innovation in REEs, facilitated by the GCP, substantially enhances not only the enterprise value but also the environmental performance of the participating companies. Our findings offer a novel perspective for research related to green innovation within the context of the GCP. This could further contribute to the realization of green development strategies and the construction of a low-carbon society. [ABSTRACT FROM AUTHOR]

Replacing conventional fossil fuel power plants with large-scale renewable energy sources (RES) is a crucial aspect of the decarbonization of the power sector and represents a key part of the carbon-neutral strategy of China. The high penetration rate of renewable energy in the electricity system, however, implies the challenges of dealing with the intermittency and fluctuation of RES. Power to gas (P2G), which can convert surplus renewable power into a chemical form of energy (i.e., synthetic gas), can help handle this challenge and supply new energy carriers for various energy sectors. By modeling three potential 2060 energy mix scenarios in China, this paper aims to describe the possible contribution of the high penetration rate of renewable energy combined with P2G in the future sustainable energy system. Different schemes are listed and compared, and the results are used in a basic economic evaluation of the synthetic gas production cost for the P2G plants. Ideally, nearly 18 million tons of carbon dioxide would be recycled and transformed into methane (around 9.37 km3) annually in China. Considering a zero price for the excess renewable power and future costs of the components, the levelized cost of energy (LCOE) of the final production of methane is estimated at 0.86 $/m3SNG. [ABSTRACT FROM AUTHOR]

The world faces several problems related to natural gas resource rents and energy production from renewable sources. One of the main problems is the influence of energy imports, manufacturing exports, and alternative energy sources on natural gas and electricity production from renewable sources. Energy imports, manufacturing exports, and alternative energy sources can impact natural gas and electricity production. This paper examines natural gas resource rents and electricity production from renewable sources nexus from 1971 to 2021, using energy imports, manufacturer's exports, and alternative energy sources in China. Electricity production from renewable sources and manufacturing exports are negatively associated with natural gas resource rents. Energy imports and alternative energy sources positively relate to natural gas resource rents in China. These results suggest that the energy sector in China is highly interconnected and that policies that seek to promote renewable energy sources and other alternatives can positively affect natural gas resource rents. China needs to develop an energy policy considering the policy implications of energy imports and natural gas resource rents. Such a policy should focus on increasing domestic production, reducing energy imports, and ensuring adequate revenue from natural gas resource rents. Additionally, regulations could be implemented that support the development of alternative energy sources, such as requiring utilities to purchase a certain percentage of their power from renewable sources. [ABSTRACT FROM AUTHOR]

This paper intends to look into the time-varying dynamic impact of US fuel ethanol, one of the renewable energy sources, on the prices of agricultural products (specifically corn, soybeans, rice, and wheat) in China based on monthly price data from January 2000 to January 2023. To achieve this, a time-varying parameter vector autoregressive (TVP-VAR) model is employed, which takes into account structural changes in emergencies through time-varying parameters. The empirical results show that the equal-interval impulse responses of price fluctuations in agricultural commodities are primarily positive to variations in fuel ethanol prices and production. And the intensity and direction of the effects vary at distinct time lags. Additionally, the magnitude of these responses is most pronounced in the short term for all agricultural commodities except for corn, and the duration of the impulse responses at different time points is generally longer for corn prices compared to other commodities. The study also reveals that the influence of US fuel ethanol on Chinese agricultural commodity prices is not substantial on the whole. Therefore, there is a necessity to advance the growth of biofuels and provide policy support and financial subsidies for agricultural products earmarked for food production. These actions could shed insights into the progression of Chinese renewable energy and food policies, ensuring the stability of the market in the long run. [ABSTRACT FROM AUTHOR]

Industrialized aquaculture is an essential trend for aquaculture development in China, owing to its considerable advantages in lower water consumption, higher productivity, and sustainability. However, information on its current status has been scarce up to now. This paper reviewed the current status and has identified existing problems as well as proposing possible solutions for the development of industrialized aquaculture in China. This field is still at an early stage of development and is mainly distributed in coastal regions. Major constraints on industrialized aquaculture include high capital and operational costs, the uncompetitive market price of aquatic products, uneven distribution of production and farming areas, a lack of suitably experienced managers and operators for recirculating aquaculture systems, and the coronavirus disease 2019 (COVID-19) pandemic. Possible solutions to these problems include technological innovations in systems optimization, the use of renewable energy sources and biofloc technology, the pollution-free certification of industrial aquaculture products, increased numbers of professionals in water quality control and waste management, and the financial assistance to companies and farmers along the aquaculture industrial chain. [ABSTRACT FROM AUTHOR]

This paper examines the long-term and short-term relationships between renewable energy consumption, output and export, and CO2 emissions in China over the period 1990–2020 from the perspective of industry and agriculture using econometric methods. The results of the study found that there is a long-run relationship and there is a causality between these variables, indicating that renewable energy consumption, output, and export are related to CO2 emissions. Specifically, from a long-term perspective, the results of co-integration and causality reveal that there is a two-way causal relationship between renewable energy consumption, output, export, and CO2 emissions, supporting the feedback hypothesis; that is, output and export have an adverse impact on the environment, while renewable energy consumption has a favorable impact on the environment. In the short term, there is a direct or indirect one-way causal relationship between export, CO2 emissions, and renewable energy consumption, which supports the growth hypothesis. The impulse response analysis has further verified the causality test results and supported this hypothesis. However, there is a strong negative correlation between industrial and agricultural export and renewable energy consumption, which will cause the use of renewable energy to fail to meet the peak demand for industrial and agricultural export in the short term. Conversely, large amounts of fossil fuels will be consumed to meet output and export demand. Therefore, on the road to social, economic, and environmental sustainability, it is necessary to consider the impact of economic growth and energy consumption (renewable and non-renewable energy) of related industries on CO2 emissions, which also provides a strong basis for the development and reduction of China's renewable energy and the long-term implementation of the emission control policy. [ABSTRACT FROM AUTHOR]

Poor access to modern energy services, or energy poverty, continues to be a significant barrier to socioeconomic progress and well-being. The complicated connections between public investment, incentives, supplier chains, and the financial success of energy poverty alleviation efforts are explored in this paper. This research examines the history of eradicating energy poverty worldwide, particularly in China. It examines how these aspects affect the efficiency and long-term viability of reducing energy poverty initiatives. This research synthesizes the evidence on government expenditure patterns and their impact on initiatives to reduce energy poverty via an extensive literature examination. The development of infrastructure, capacity building, and the deployment of energy technology are all made possible in large part by government spending. Financial and regulatory incentives have also been shown to encourage the energy industry's private sector engagement and innovation. These incentives help expand underprivileged groups' access to electricity by creating an atmosphere conducive to investment. This research also examines supply chains' crucial role in combating energy poverty. For the effective installation and upkeep of energy projects, efficient and resilient supply chains are crucial because they guarantee the availability of vital materials and resources. An integrated supply chain strategy may improve project results, save costs, and eliminate risks related to logistical difficulties. Government funding, incentives, and supply chains all have a connection that affects how well energy poverty alleviation programs function financially. Maintaining projects after their first execution requires sustained financial performance. It explores how supply network interruptions may affect financial performance, highlighting the need for robust supply chain management techniques. As a result, this study adds to a comprehensive knowledge of the complex processes underpinning the reduction of energy poverty. It offers insights into developing efficient policies and strategies by examining how government actions, incentives, supply chains, and financial performance interact. These observations are relevant for practitioners, investors, and academics trying to increase access to sustainable energy sources and reduce poverty in addition to policymakers. This report provides helpful recommendations for boosting the effectiveness and endurance of energy poverty reduction activities as nations work to reach global sustainable development objectives. [ABSTRACT FROM AUTHOR]

Based on the background of comprehensive green transformation of economic and social development, this paper selects panel data of 30 provinces in China from 2000 to 2019, uses the panel fixed effects model and panel threshold effect model, and discusses the nonlinear correlation mechanism between green investment, industrial structure, renewable energy, and low-carbon development of the transportation industry. The results show that, firstly, industrial structure and renewable energy can significantly promote the low-carbon development of the transportation industry, while green investment has a restraining effect on it (the main reason is that currently its scale is small and its investment in the transportation industry is relatively low). Secondly, industrial structure and renewable energy have a negative moderating and threshold effect in the process of green investment restraining low-carbon development of the transportation industry. Thirdly, these threshold effects have obvious regional heterogeneity characteristics. Based on this, decision-makers should not only continue to expand the scale of green investment and optimize resource allocation but also fully utilize the threshold characteristics of industrial structure and renewable energy in different regions to develop different strategies and achieve the promotion of green investment in low-carbon development of the transportation industry as soon as possible. [ABSTRACT FROM AUTHOR]

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO2) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO2 emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO2 emissions; correspondingly, this study builds a model for CO2 emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO2 emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO2 emissions. Finally, this study forecasted a CO2 emission trend, with a slowdown predicted in China by 2022; however, CO2 emission's reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO2 emissions without harming economic development. [ABSTRACT FROM AUTHOR]

Governments actively encourage renewable energy use to deal with climate change and achieve carbon emission reduction targets. It is crucial to find out the driving factors that affect the utilization of renewable energy. Therefore, based on China's 2010–2016 input–output table, this paper uses the input–output model and structural decomposition analysis (SDA) to analyze the driving factors of renewable energy changes in the production end, household end, and the aggregate economy. The results show that the changes in the consumption structure (F) is the most crucial factor for renewable energy use, followed by technology progress (T) and final demand per capita (V). Sector SEHW (supply of electric power, heat power, and water) and MCRP (manufacture of coke and refined petroleum products) are the two vital sectors to achieve China's energy transition of the production level. However, as for households, the proportion of renewable energy has been declining. Hence, the government should promote renewable energy use and achieve the green transition in production and household levels. [ABSTRACT FROM AUTHOR]

In the context of internal circulation, domestic trade is widely encouraged in China. However, the growth of inter-provincial trade may aggravate inter-regional embodied carbon emissions transfer. The knowledge about the causes of changes in embodied carbon emissions from an industry transfer perspective is limited, which is significant for achieving the regional carbon emission reduction fairly and reasonably. Therefore, this paper utilizes the provincial energy consumption data and the multi-region input–output tables in 2002 and 2012 to calculate the embodied carbon transfer among different regions. Furthermore, the inter-regional embodied carbon emissions transfer trends are analyzed and discussed by the quantitative measurement of industries transfer. The results indicated that nearly 58% of carbon emissions were transferred out from the southeast coastal areas to the central and western areas by importing carbon-intensive productions, reaching 516 million tons. In addition, the carbon intensity in the eastern areas decreased by about 30%, while that increased by 11% in the central and western areas. Energy inequality among regions was getting worse. To promote inter-regional development equity, the emission reduction targets of different regions should be heterogeneous. Specifically, the southeast coastal areas are suggeted to compensate for the transfer-out emissions. The central and western areas are suggested to develop markets for renewable energy topromote the economy and adjust energy structure. [ABSTRACT FROM AUTHOR]

Understanding the intrinsic mechanism behind changes on energy intensity provides insights about reducing carbon emissions and promoting the sustainable development of Beijing-Tianjin-Hebei (BTH) region. Although various studies have found a causal relationship between energy intensity and energy-related carbon emissions, the internal mechanisms are still unclear. This paper presents a comprehensive analysis of the impact of energy intensity on carbon emissions from 2005 to 2015. With an association established between logarithmic mean Divisia index (LMDI) and generalized Fisher index (GFI), two-layer factor decomposition model is proposed to explore the factor analysis in-depth. (1) LMDI method proves that energy intensity is the main contributor that reduces carbon emissions in BTH. (2) GFI model further decomposes energy intensity into five effects, namely energy substitution, technology progress, labor productivity, capital substitution, and labor-capital resources allocation. (3) The results reveal that the effect of capital-energy substitution in declining energy intensity surpasses technology progress. (4) Energy-labor substitution has increased energy intensity, while energy-energy substitution is negligible. For the coordinate development of BTH, the government should aim at energy intensity and attach importance to encouraging entrepreneurship, accelerating the construction of carbon trading market, allocating resources rationally, and guiding the capital flow into energy-efficient direction. [ABSTRACT FROM AUTHOR]

Stimulating renewable energy consumption has become a major strategic choice for China to both fulfill the international commitment to reduce carbon emissions and realize the high-quality growth of the domestic economy. On account of the provincial data during the period of 2000 to 2017, we creatively incorporate the ecological footprint into the measurement of low-carbon economy development level through super-efficient SBM model, so as to infer the coordinated development level of 3E system more precisely. Based on the factor substitution effect, energy path dependence effect, and scale effect, the complex nonlinear relationship between the two core research objects is further probed by constructing the threshold regressive model. On the foundation of theoretical research, the consumption of renewable energy, the intensity of energy use, and the level of regional economic development are respectively selected as the moderating variables of the model. Further, we divide different intervals of threshold values to distinguish the differences in the effects caused by regional heterogeneity. The following conclusions are drawn ultimately: There is an apparent threshold effect between renewable consumption and the advancement of the low-carbon economy. Only when renewable itself reaches a higher level of consumption can it show a significant advantage in green economic development. In addition, to make full use of renewable resources to boost the low-carbon and green economy, it is necessary to reduce the economy's dependence on energy, that is, to decrease the intensity of energy use while maintaining the process of improving coordination of regional economy. [ABSTRACT FROM AUTHOR]

This study investigates the feasibility of using renewable energy sources in soil remediation to advance green recovery in a way that is both sustainable and kind to the environment. The report stresses the need to reduce the adverse effects of soil pollution in China and foster economic recovery. This study aims to determine how green energy may be most effectively used in soil remediation operations. Using renewable energy sources to power remediation procedures and phytoremediation is presented in this research as two ways to achieve green recovery in soil remediation. The analysis in this work employs the unit root, auto-regressive distributive lag (ARDL), and vector error correction model (VECM) methods. Based on our research, we know that using renewable energy sources like solar, wind, and geothermal power may significantly lessen the environmental impact of soil remediation while simultaneously advancing the cause of sustainability. Phytoremediation is a low-cost, environmentally friendly option that utilizes plants to degrade and remove soil pollutants. The study's findings also stressed the need to consider various remediation strategies' advantages and disadvantages. The study's findings also exposed the potential advantages and disadvantages of phytoremediation, as was the method's viability for use in extensive soil remediation initiatives. The report concludes by emphasizing the need to assess soil remediation and green recovery's more enormous social and environmental implications. We can build a more sustainable future, encourage economic recovery, and combat environmental degradation using renewable energy sources and cutting-edge remediation techniques. The article suggests doing more studies to learn more about the pros and downsides of combining soil remediation and green recovery initiatives. [ABSTRACT FROM AUTHOR]

Amidst resource loss and environmental protection constraints, achieving green development necessitates enhancing green total factor productivity (GTFP) as a means of promoting rational and efficient resource allocation, thereby balancing economic growth and environmental preservation. Meanwhile, literature on the subject matter of GTFP from a sustainability viewpoint is minimal. As a result, this study employs the panel dataset from 30 provinces of China spanning the period 2005 to 2020 and utilizes the method of moments quantile regression (MMQR) developed by Machado and Santos Silva (2019) to analyze the heterogeneous role of green innovation, environmental regulations, and fiscal expenditure on GTFP. Moreover, the controlling variable for this study includes renewable energy and economic growth. Furthermore, this study investigates the heterogeneous combined impact of green innovation and fiscal expenditure (GTE*FSE) on GTFP. The findings of the MMQR reveal that green innovation has a positive impact on GTFP, while fiscal expenditure, environmental regulations, and renewable energy consumption have a negative impact. GTE*FSE has a positive and significant effect on GTFP, indicating that FSE can reinforce and increase the positive impact of GTE on GTFP in the long run. The study also reveals that economic growth has a mixed effect on GTFP, depending on the quantiles. Furthermore, environmental regulation has a significant and negative impact on GTFP, contradicting the Porter hypothesis. Likewise, the robustness of the findings is confirmed by the results of the fully modified OLS (FMOLS) and dynamic OLS (DOLS) estimations, which indicate a similar impact of the determinants on GTFP as observed in the MMQR analysis. This reinforces the validity of the findings and suggests that the observed relationships are robust to different estimation techniques. Furthermore, the findings of the Dumitrescu and Hurlin (D-H) panel causality test reveal significant bidirectional causality between renewable energy consumption and GTFP and fiscal expenditure and GTFP. Policy-makers need to channel a large chuck of their fiscal spending into green innovation so as to boost sustainability. [ABSTRACT FROM AUTHOR]

This study uses a quantitative methodology to investigate how the rise of digital money has affected efforts to increase green energy use in China. This work contributes to the body of knowledge by using a number of empirical methods, such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. This study's results further demonstrate the importance of digital financing in easing the adoption of renewable energy sources throughout China. Financing alternatives for renewable energy projects have increased as a result of digital finance's integration of digital technology with financial services. A wider range of investors has been attracted through crowdfunding, peer-to-peer lending, and other alternative financing models made possible by digital platforms, allowing the development of small and medium-sized renewable energy projects that may have had trouble securing funding through more traditional channels. The impact of digital finance on energy management and optimization is also investigated. As a result, renewable energy sources have been more widely adopted due to increased energy efficiency, better grid integration, and more efficient energy delivery. This study presents substantial evidence of the beneficial benefits of digital finance on renewable energy use in China using rigorous empirical methodologies such as regression analysis, parametric quantile estimation, stability diagnostic tests, and sensitivity analysis. The results highlight the significance of using digital money to boost the use of renewable energy, lessen reliance on fossil fuels, and help create a greener, more sustainable future. [ABSTRACT FROM AUTHOR]

The Belt and Road Initiative (BRI), spearheaded by China, is anticipated to bolster trade, investment, and economic growth among participating countries to advance the United Nations' Sustainable Development Goal 7 through international trade. Within this context, renewable energy has emerged as a promising avenue to address environmental degradation and foster sustainable development. However, the impact of BRI's trade volume on renewable energy development and adoption in these nations remains unresolved. To address this, our study examines the influence of trade openness, foreign direct investment, economic growth, and oil prices on renewable energy consumption in 94 BRI countries with varying income levels from 2000 to 2019. Employing panel data analysis, including fixed effects (FE), random effects (RE), and the system generalised method of moments (GMM), we present findings across income groups: i) Trade openness exhibits a positive effect on renewable energy consumption in high-income and upper-middle-income countries; ii) In contrast, it diminishes renewable energy consumption in lower-middle-income countries; iii) Trade openness demonstrates insignificant effects on renewable energy consumption in low-income countries; iv) On the panel level, trade openness significantly and positively impacts renewable energy consumption. Our research underscores the significance of trade openness as a crucial instrument for advancing renewable energy development in high-income BRI countries, thereby fostering environmental sustainability. Policy interventions targeting renewable energy hold promise for enhancing environmental quality in low-income countries. [ABSTRACT FROM AUTHOR]

As the globe transitions to a low-carbon economy, China's renewable energy (RE) sector is crucial to attaining sustainable growth. Green financing and corporate social responsibility (CSR) strategies have become increasingly important in promoting the growth and sustainability of the RE sector. In order to evaluate CSR factors and green finance strategies for effective integration in supporting the RE industry, this research employs hybrid Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy VIekriterijumsko KOmpromisno Rangiranje (FVIKOR) approaches in the context of China. The FAHP method is used to determine the various CSR factors and subfactors, while the FVIKOR method is employed to prioritize the key green finance strategies. The findings of the FAHP method highlight the importance of socioeconomic development, environmental protection, and stakeholder engagement as critical CSR factors for RE sectors. Moreover, the results of the FVIKOR method reveal that innovative financing mechanisms, green bonds, and green banks emerged as significant green finance strategies for mobilizing capital and resources for RE projects. The study highlights the value of aspects of CSR and green financing techniques in fostering sustainable development in the RE industry. The results can aid in the promotion of sustainable practices and the assistance of China's transition to a more resource- and environment-wise economy by firms, investors, governments, and other stakeholders. [ABSTRACT FROM AUTHOR]

The impact of digital finance on green bonds and clean energy sources is analyzed. So, the primary objective of this study is to create a unique time-varying causality test to identify the relationship between ecological consciousness and green technology, clean energy, and digital currency. The China region was established using data from 2001 to 2019. A dynamic connection model with spillover is employed to further guarantee stability. The empirical findings reveal that the clean energy to digital finance index (30.544%) and the clean energy to green economy index (30.544%) are the sources for the spillover shocks analysis. because the overall dynamic connection of assets throughout time is affected by financial events. For every additional percentage point that renewable energy sources are employed, long-term environmental costs are lowered by 0.68%. And yet, the transition from renewable energy to digital finance has been characterised by increasing instability and causal significance as it has advanced. The organizational environment is shown to have the second-greatest influence on the growth of the green bond market, behind the state of the local economy and environmental governance. Increasing the marketability of clean energy securities requires stable, predictable legislation that improves our knowledge of the risk profile of these investments. [ABSTRACT FROM AUTHOR]

There has always been controversy over how renewable energy technologies can play a role in reducing carbon emissions. Based on the energy patent data and the economic data of 244 prefecture-level cities from 2007 to 2017 in China, we explore the carbon reduction effect of renewable energy technology and its mechanism from the perspective of energy production, conservation, and management. The two-way fixed effect, instrumental variable, spatial Durbin, and mediation effect models are employed to explore empirical results. We found that (1) the impact of renewable energy technologies on carbon emissions is nonlinear, with an inverted U shape. However, this inverted U-shaped relationship only exists locally in cities and there are uncertainties in adjacent cities, which indicates that cross-regional cooperation in renewable energy technology needs to be improved. (2) The mechanism analysis shows that industrial agglomeration and energy consumption scale are the channels that renewable energy technologies affect carbon emissions. Thus, the implicit carbon emissions generated by industrial agglomeration and the failure to green upgrade energy consumption are the main reasons for the inverted U-shaped relationship. (3) The carbon reduction effect of renewable energy technologies of conservation type takes effect first, and renewable energy technologies of production type do not reduce carbon emissions in non-eastern cities, which means that non-eastern cities are likely to become pollution havens. This study provides evidence for renewable energy technologies to achieve efficient carbon emission reduction and cross-regional technical cooperation. [ABSTRACT FROM AUTHOR]

China's rapid economic growth in recent decades has caused a growing problem of environmental pollution, which negatively impacts the physical and mental health of residents. In recent years, renewable energy has emerged as a promising solution to alleviate environmental pollution and improve residents' well-being. However, it is unknown whether renewable energy development can counterbalance the health impacts of environmental pollution. Therefore, we conducted a study using data from the China Family Panel Studies (CFPS) to examine the impact of environmental pollution and renewable energy on the health of 20,694 residents. Our analysis showed that renewable energy development can partially offset the negative health effects of environmental pollution. Specifically, we found that a 1% increase in environmental pollution is linked to an average decrease of 0.0911% in physical health (PHY) and 0.0566% in mental health (MEN), whereas each 1% rise in renewable energy corresponds to an average increase of 0.2585% in PHY and 0.1847% in MEN. These positive effects apply to male and female residents, urban and rural residents, young and middle-aged adults, and people with low, medium, and high levels of education. These findings are significant for decision-makers striving to improve Chinese residents' physical and mental health by considering the specific impact of renewable energy and comprehensive environmental pollution. [ABSTRACT FROM AUTHOR]

This research investigates the resource curse hypothesis and environmental sustainability by integrating China's natural resources, renewable energy, and urbanization. However, the EKC N shape describes the complete picture of the EKC hypothesis for the growth-pollution relationship. The findings of FMOLS and DOLS show that economic expansion positively drives carbon dioxide emissions in the beginning, then negatively so after the target level of growth is reached. Continuing economic expansion in China does not maintain the intended level and again has a beneficial impact on the country's carbon dioxide emissions. However, the EKC U, inverted U, and N shapes persist in the growth-pollution connection over the long term. Although adopting renewable energy and urbanization help reduce carbon dioxide emissions, the formation of fixed capital worsens environmental conditions. Natural resource rents are a major cause of environmental degradation and the resource curse that has plagued China. Economic growth, as well as its square and cube, has a causal effect on CO2 emissions, as shown by the frequency domain causation. Carbon dioxide emissions at frequencies of 0.05, 1.50, and 2.50 are momentarily predicted by the use of renewable energy and urbanization. The investigation recommends switching to renewable energy sources owing to low cost and the potential to limit the overuse of non-renewables. To balance the overdo of natural resources and ensure continued long-term growth-environment sustainability, technological advancement is recommended as a countermeasure as a mitigating mechanism. [ABSTRACT FROM AUTHOR]

The objective of this study is to examine how digital finance influences renewable energy performance in China. Empirical data from China between 2007 and 2019 is used to evaluate the relationship among these variables. The study uses two techniques, quantile regression (QR) and generalized methods of moments (GMM), to draw empirical conclusions. The results reveal that digital finance significantly influences the renewable energy performance, ecological growth, and financial performance of cities in China. Specifically, digital finance accounts for 45.92% of the variation in renewable energy indicators, 27.60% in ecological growth, and 24.39% in the improved financial performance of renewable energy at the city level. The study also observes that the city-level score for digital finance, renewable energy, and other indicators is heterogeneous in movement. Factors contributing to this heterogeneity include high population (16.05%), access to digital banking (23.11%), province-level renewable energy performance (39.62%), household financial stability (22.04%), and household renewable energy literacy (8.47%). Based on these findings, the study recommends practical implications for key stakeholders. [ABSTRACT FROM AUTHOR]

As the largest carbon emitter in the world, with its transportation sector contributing the largest shares of its emission, the need for a low-carbon transition economy has become a policy agenda for China because in order to reach carbon neutrality by 2050, lowering the intensity of carbon emissions in the transportation sector will be crucial. In this regard, we used the "bootstrap autoregressive distributed lag model" to explore the impact of clean energy and oil prices on the intensity of carbon emissions in China's transportation sector. The study found that an increase in oil prices decreases the intensity of carbon emissions in the short and long run. Similarly, an increase in the level of renewable energy and economic complexity declines the intensity of carbon emissions in the transportation sector. On the contrary, the research demonstrates that non-renewable energy contributes positively to carbon emission intensity. Therefore, the authorities must promote green technology to neutralize the transportation system's detrimental effects on China's environmental quality. The implications for successfully promoting carbon emission intensity mitigation in the transportation sector are examined in the conclusion. [ABSTRACT FROM AUTHOR]

Renewable energy has an established role in improving environmental quality and economic growth. However, the nexus between renewable energy, education, and employment have yet to be disclosed in detail. Therefore, our primary focus in this analysis is to investigate the impact of renewable energy investment and education on the employment level in China. The empirical analysis is based on the novel quantile autoregressive distributed lag (QARDL) technique that can measure the estimates across quantiles. From the estimates of the QARDL model, we confer that renewable energy investment and education significantly and positively impact the employment level in China in the long run. In short-run, renewable energy investment does not have any noticeable impact on the employment level, while the rise in the education level help increases the employment rate in China. Moreover, the long-term positive impact of economic growth and information and communications technology (ICT) is more pronounced. [ABSTRACT FROM AUTHOR]

In recent times, the concept of green growth has emerged, which has a critical part to play in controlling the environmental impact of economic activities. In this analysis, we have explored three determinants of green growth: green finance investment, technological capital, and renewable energy. Moreover, this study focuses on the asymmetric impact of green finance investment, technological progress, and renewable energy on green growth in China during the period spanning from 1996 to 2020. To get the asymmetric short and long-run estimates across various quantiles, we have employed the nonlinear QARDL. The long-run estimates attached to a positive shock in green finance investment, renewable energy demand, and technological capital are positively significant at most quantiles. While, the long-run estimates attached to a negative shock in green finance investment, technological capital, and renewable energy demand are insignificant at most quantiles. In general, the findings suggest that the rise in green financial investment, technological capital, and renewable energy demand positively impacts green growth in the long run. The study offers a range of significant policy recommendations that can contribute to the advancement of sustainable green growth in China. [ABSTRACT FROM AUTHOR]

In China, the consumption of non-renewable energy increases not only in general economic growth but also in large amounts of carbon dioxide (CO2) emissions which cause disasters and catastrophic damages to the environment. To alleviate environmental pressure, it is neccessary to forecast and model the relationship between energy consumption and CO2 emissions. In this study, a fractional non-linear grey Bernoulli (FANGBM(1,1)) model based on particle swarm optimization is proposed to forecast and model non-renewable energy consumption and CO2 emissions in China. Firstly, based on the FANGBM(1,1) model, non-renewable energy consumption in China is predicted. The comparison results of several competitive models show that the FANGBM(1,1) model has the best predictive performance. Then, the relationship between non-renewable energy consumption and CO2 emissions is modeled. On this basis, China's future CO2 emissions are effectively predicted based on the established model. The forecast results show that the growth trend of China's CO2 emissions will continue to grow to 2035, while the prediction results in different scenarios also show that that the different growth rates of renewable energy share lead to different times to peak CO2 emissions. In the end, relevant suggestions are proposed to support China's dual carbon goals. [ABSTRACT FROM AUTHOR]

Based on the data of listed renewable energy enterprises in China from 2009 to 2020, I study the impact of fintech on the sustainable development of renewable energy enterprises. The results show that fintech promotes the sustainable development of renewable energy enterprises. The mechanism tests show that fintech promotes the sustainable development of renewable energy enterprises by improving investment efficiency. The cross-sectional results show that the implementation of green credit policies and the improvement of information disclosure quality promote the positive impact of fintech on the sustainable development of renewable energy enterprises. This study enriches the literature in the field of fintech and renewable energy enterprises and provides empirical evidence and policy enlightenment for fintech to promote sustainable development in renewable energy enterprises. [ABSTRACT FROM AUTHOR]

The problem for developed and developing economies is achieving sustainable development and cleaner production. Income, institutional regulations, institutional quality, and international trade are the primary factors of environmental externalities. This research looks at 29 provinces in China between 2000 and 2020 to determine the effect of green finance, environmental regulations, income, urbanization, and waste management on renewable energy generation. Similarly, the current study uses the CUP-FM and CUP-BC for the empirical estimation. More precisely, the study shows the positive influences of environmental taxes, green finance index, income, urbanization, and waste management in renewable energy investment. However, the different measures of green finance, such as financial depth, financial stability, and financial efficiency, also positively contribute to renewable energy investment. Therefore, it can be considered the best solution to environmental sustainability. However, imperative policy implications are given to attain the peak of renewable energy investment. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources can be supported by the digitalization of energy systems, which increase dependability and lower costs of energy production and consumption. However, the energy digitalization support energy infrastructures and technologies currently in place are insufficient. This research presented the study results by using the generalized least square estimates (GLS) model and the international sample of China regions from 2003 to 2017. Main results of the dynamic fixed effect (DFE) estimator for the autoregressive distributed lag (ARDL) method, establishing ES goals for lowering energy consumption and pollution emission fosters a country's renewable energy business sector's digital transformation in the short term, while encouraging the use of renewable energy sources fosters a country's long-term digitalization efforts. Based on this, the direct effects and dynamic effects of digitalization and financial development on environmental are explored, respectively, using the panel data regression model and panel vector autoregression (PVAR) model. The threshold regression model is then used to examine the two parameters' threshold effects on eco-efficiency. An accurate estimate of the resource consumption in smart factories is made possible by the digital twin that is created using the product's and its attributes as well as manufacturing data. The results suggests the future directions for the associated stakeholders. [ABSTRACT FROM AUTHOR]

This article examines the innovation in the green sector frequently facing a financial conundrum. Production of renewable energy is the eighth sustainable development, based on the data from the 30 Chinese provinces (2000–2017). This study presents an analysis of the effects of green digital finance on green innovation on protection of environment using influence mechanism analysis. Digital finance, which has become a major driver of green innovations in China, may first increase the number and quality of green technical innovation. The results show that the promotion effect of digital finance on the efficiency of renewable energy markets is greater than the inhibitory effect, making the total effect less obviously favorable. In other results, the elasticity of lnGFDI is significant at the 5% level and is 0.1545% and 0.1880% in the present and 1-year delayed periods, respectively. Further, the average total effect of FDI on the effectiveness of green innovation is 0.008, with an average encouraging effect of 0.0051 and an average inhibiting effect of 0.0039. We conclude that diverse behavior for that policy support increases the impact of green digital finance, promote green innovation, and generate emission free environment for sustainable energy markets. [ABSTRACT FROM AUTHOR]

Significant challenges confronting China include reducing carbon emissions, dealing with the resulting problems, and meeting various requirements for long-term economic growth. As a result, the shift in industrial structure best reflects how human society utilizes resources and impacts the environment. To meet China's 2050 net-zero emissions target, we look at how technological innovations, financial development, renewable energy investment, population age, and the economic complexity index all play a role in environmental sustainability in China. Analyzing short- and long-term relationships using auto-regressive distributive lag (ARDL) bounds testing, we used historical data spanning 1990 to 2018. According to the study's findings, the cointegration between CO2 emissions and their underlying factors was found. The deterioration of the environment directly results from the financial development, increasing economic complexity, and population aging. Technical advancements, investments in renewable energy sources, and changes to the industrial structure all contribute to lower CO2 emissions. Granger causality results were also reliably obtained in this study. According to our findings in the fight against environmental problems, a key tool for meeting long-term sustainability goals is policy prescriptions that use technological innovations, renewable energy investment, and industrial structure. [ABSTRACT FROM AUTHOR]

The multi-renewable energy complementary system (MRECS) is a good plan that can effectively support the accomplishment of carbon peaking and carbon neutrality on schedule and take full advantage of renewable resources in rural areas. This research investigates the techno-economic feasibility of MRECS in rural areas to promote its large-scale implementation. A MRECS with integrated solar, wind, and biomass energy is proposed for a rural economic development zone. First, a scientific evaluation of the potential for renewable resources in rural areas is done. Second, a case study of the Jize Economic Development Zone is applied to examine the optimal MRECS configuration. Finally, an economic evaluation model that takes environmental benefits into account was created based on life cycle costs (LCCs). For the techno-economic analysis, the net present value (NPV), dynamic investment payback period, and internal rate of return (IRR) are also employed. Findings reveal that (1) the Jize Economic Development Zone has considerable development potential due to its abundance of renewable energy resources and ability to plan for 168.42 MW of renewable energy units; (2) to meet the demand for continuous power generation and realize the sensible use of renewable energy, a combination of 10 MW photovoltaic power generation (PV), 25 MW wind power generation (WT), 2 MW biogas power generation (BG), and 1 MW straw direct combustion power generation (SDC) is able to be implemented; (3) the provided renewable energy system can save indirect expenses up to 10.60 million RMB/year, with significant environmental advantages, when compared to grid extension; and (4) the NPV of the dynamic investment reaches RMB 322.44 million after accounting for the environmental advantages in the income of MRECS. The dynamic investment payback period is 6.42 years, and the IRR is 21.44%. According to the findings, the MRECS is economically viable, and capitalizing on the environmental advantages can increase those advantages even more. [ABSTRACT FROM AUTHOR]

This study analyzed the determinants that impact innovation on offshore wind energy (OSW) for a select group of countries, applying mixed-method approaches for a period between 2011 and 2021. The OSW sector witnessed cost reductions in recent years; therefore, this study analyzed how these factors impact technological innovation in the OSW sector. The fixed effects results proved trademark, carbon emissions, offshore wind capacity, and electricity from renewable energy, technical and scientific journals are significant and impact innovation regarding offshore wind energy. The maximum likelihood (MLE) coefficients are more robust than the restricted maximum likelihood (MREL) and better explained the significance of the variables in spurring OSW innovation. Ultimately, the interaction term "cross" came out significant in the analysis. It signified the importance of the interaction variables in scaling innovation. Similarly, the study forecasted OSW capacity additions to grow to more than 28GW by 2036, at a 48.8% growth rate, from the current over 55 G.W. capacity. Additionally, the infrastructure development of the OSW sector via a fitted line between total global offshore capacity and the development projects observed a negative relationship among these dual factors evaluated in the OSW, showing a decreasing trend of capacity additions among countries, as well as the fitted line relationship between total country OSW capacity and operational projects showed that China leads the globe with operational OSW projects. At the same time, Brazil is the new leader in the world regarding OSW capacity. The general analysis of the parameters of the OSW infrastructure plan showed the sector is declining regarding secured projects, development projects, operational projects, and capacities additions in some countries. However, global total capacity additions are on a steady path, declining a bit. This is attributable to the pandemic that slowed the global economy. This study will serve as a reference document for policy formulators regarding scaling up innovation for offshore wind energy. [ABSTRACT FROM AUTHOR]

Renewable energy is considered vital to addressing the issue of climate change and energy poverty. In recent times, empirics have tried to find the determinants of renewable energy consumption. Hence, the primary focus of the analysis is to estimate the impact of financial integration, education, and ICT on renewable energy consumption in China. In order to get the estimate of the variables, the analysis has applied the quantile ARDL model. The long-run estimates of the financial integration are positively significant at most quantiles, confirming the positive impact of financial integration on renewable energy consumption. Similarly, the long-run estimates of ICT are positively significant in almost all quantiles, confirming that digitalization helps increase renewable energy consumption in China. The long-term effect of education is significant at the higher quantiles. In the short run, the estimated coefficients of financial integration are positively significant at almost all quantiles; however, the estimated coefficients of ICT are positively significant in half quantiles. The short-run results of education are insignificant at most quantiles. In line with these results, several appropriate financial integration, digitalization, and education policies are recommended. [ABSTRACT FROM AUTHOR]