Transformation Of Energy Structure Research Articles

The influence effect of regional carbon emission reduction under the perspective of fiscal decentralization: Government intervention or market mechanism?

AbstractBased on the perspective of fiscal decentralization, the study focuses on 30 provinces in China and employs various econometric models including the threshold model, spatial econometric model, mediation model, and regulation model. The research findings indicate that fiscal decentralization has a double‐threshold effect on government intervention, market mechanisms, and regional carbon emission reduction. Both government intervention and market mechanisms have inhibiting effects on carbon emission, with significant coefficients of GOVI and MARM at the 1% level. The cooperation between government intervention and the market mechanism effectively limits carbon emissions. Government intervention facilitates regional carbon emission reduction through the construction of new infrastructures and energy structure transformation, yielding a significant intermediary effect. The market mechanism is positively regulated through green finance and technology innovation to promote regional carbon emission reduction. Moreover, government intervention enables the market to achieve carbon emission reduction more effectively, especially in areas with a higher degree of government intervention. Continuous improvement and upgrading of regional and national carbon markets are essential to attain the carbon peak and carbon neutrality goals. Furthermore, attracting more participants to these markets for emission control subjects is necessary to enhance the effectiveness of government–market coordination.

Rural household nonagricultural income and energy transition: Evidence from central China

Promoting China's energy transition is essential for achieving low-carbon development and achieving the nation's carbon neutrality target. Previous research has primarily focused on industrial production energy consumption transition paths, and rural household energy consumption has rarely been investigated. This study focuses on the impact of nonagricultural income on rural household energy consumption in the Huang-Huai-Hai region using questionnaire data, examining the contribution of rural households' nonagricultural income to the energy consumption transition (i.e., from dirty energy sources such as firewood to clean energy sources such as liquified petroleum gas (LPG)). Instrumental variable two-stage least squares (IV-2SLS) estimation and IV-tobit models are applied to solve potential endogeneity problems. The results demonstrate that nonagricultural income can promote rural households' energy structure transformation, increase spending on clean energy such as LPG and electricity, and decrease expenditure on dirty energy sources such as coal and firewood. Further examination reveals that nonagricultural income can enable rural households to afford modern necessities and transition to cleaner, more efficient energy. The study proposes promoting rural energy structure transformation to boost sustainable development and increase nonagricultural income. Strengthening skills training, encouraging more off-farm employment, and other approaches will diversify rural households' income.

Will artificial intelligence make energy cleaner? Evidence of nonlinearity

Energy plays a vital part in stimulating economic progress, and the shift towards a cleaner energy system is highly significant for ensuring the sustainable development of the economy. China's energy structure urgently needs to be transitioned. The fast advancement and implementation of artificial intelligence (AI) has provided a new and important tool for promoting the transition of energy structure. So, what is the relationship between the application of artificial intelligence and the transition of the energy structure? This research introduces artificial intelligence into the energy sector, focusing on the relationship between artificial intelligence and energy transition. Since nonlinear models are better able to study the complex effects and phase differences of artificial intelligence. Using China's provincial panel data spanning from 2006 to 2019, this study employs nonlinear modeling to explore the stage differences in the process of AI in facilitating energy structure transformation. This paper derives the following findings based on empirical research. First, there is a U-shaped relationship between artificial intelligence and the transition of energy structure. Specifically, before the inflection point, the initial application of artificial intelligence, artificial intelligence may adversely impact energy transition. When the inflection point is passed, AI will help facilitate the energy transition. Second, the U-shaped relationship between AI and energy transition is more pronounced in coastal and non-resource-based regions. Third, energy intensity, government investment in science and technology, and informatization will moderate the U-shaped relationship between artificial intelligence and energy transition, changing the steepness of the original U-shaped relationship and even reversing it. Hence, it is imperative to effectively utilize the technological benefits of artificial intelligence through the development patterns and distinctive features of different regions, thereby facilitating the smooth transition of the energy structure.

Research on vehicle speed prediction model based on traffic flow information fusion

Resource scarcity, global climate change and environmental pollution are increasingly constraining the development of the automotive industry. China proposes to reach the carbon peak by 2030; to reach the carbon neutral double carbon target by 2060 and gradually promote a green and low-carbon transition in energy development. The development of new energy vehicles is an important approach for China to realize its energy structure transformation in the automobile industry. HEV, as a transitional product of automobile energy transformation, has the advantages of both internal combustion engine vehicles and electric vehicles, which can improve the fuel efficiency and the emission problem of internal combustion engine vehicles and the range is longer compared to electric vehicles. One of the important aspects of HEV research is the design of whole vehicle energy management strategy based on the model predictions. Particularly, model-based predictive control is one of the mainstream energy management strategies nowadays, and its optimization effect is mainly subject to the model prediction accuracy. In this study, we constructed the ITS environment of a local roadway through simulation, compared the speed prediction effects of different speed prediction methods in different prediction time domains, and fused the historical information of vehicles (speed of the vehicle in front, distance, signal status, distance, and remaining time). It is found that N-BEATS is more effective in predicting vehicle speed in different prediction time domains, and the prediction accuracy of the speed prediction model is effectively improved after its fusion of multivariate information.

Financial openness and energy structure transformation

Energy structure transformation is the only way for China to achieve the “dual carbon” goal, and one of the difficulties faced by energy transformation is financing. In the context of China’s steadily promoting the high-level opening-up of financial industry, this paper uses the panel data of China’s provincial level from 2010 to 2019 to systematically examine the impact of financial opening-up on the transformation of energy structure. The results show that: 1) Financial openness has a significant positive impact on the energy structure transition; 2) In different stages of energy structure transformation, as the main driving force in the initial stage of energy structure transformation is the government’s policy support, with the continuous maturity of energy structure transformation, the impact of financial openness on energy structure transformation gradually increases; 3) With different levels of economic development, the driving effect of financial openness is also different. The lower the level of economic development is, the stronger the driving effect of financial openness on energy structure transformation is due to the lack of financing channels. This paper provides a theoretical basis for China’s energy structure transformation, and also provides rich policy implications for promoting China’s financial industry to open up at a high level.

Regional productivity in the transformation of China’s energy structure –estimation of the restricted cost function

ABSTRACT In this study, energy structure is introduced into the restricted cost function to study the influence of energy structure transformation (EST) on regional productivity. The analysis indicates that: (i) the average annual productivity of various regions in China has a positive growth, with an average annual growth rate of 6.97% and a downward growth trend from 12.15% to 4.13%. Technological progress has the greatest positive contribution to productivity growth, while energy structure and scale effect have slight negative effects. (ii) Further regional empirical analysis reveals a gradient distributions of eastern > central > western area for productivity growth. Although the effect of technological progress in western area is greater than that of eastern and central areas, low energy efficiency has dragged down its productivity growth. (iii) Factor input bias analysis demonstrates that technological progress tends to factor saving, while energy structure adjustment tends to a slight factor using with different preferences in regions. Inspired by the empirical results, strategies for optimizing policies and regional collaboration are proposed from a systematic perspective.

Synergizing policies for carbon reduction, energy transition and pollution control: Evidence from Chinese power generation industry

To mitigate climate change and achieve sustainable development, Chinese governments have introduced “1+N” “dual-carbon” policy system aimed at reducing CO2 emissions, transforming energy structures and controlling pollution. An effective policy mix and synergy is crucial for achieving the emission reduction targets and for ensuring the effectiveness of the policies, and it is therefore of great practical importance to provide a pathway for policy synergy based on assessing policy effectiveness. This paper selects three policies, namely the carbon Emission Trading System (ETS), Coal Control and Clean Utilization (CCCU), and Green Financial Reform and Innovation Pilot Zone (GFPZ), sets up ten scenarios, adopts difference-in-differences (DID) models to evaluate the impact, and give a pathway for policy synergy. The results show that ETS, CCCU, and GFPZ policies have significant positive effects on carbon emission reduction, energy structure transformation, and industrial environmental pollution control, respectively; CCCU has synergistic effects with ETS and GFPZ policies in controlling coal consumption and increasing the completion of industrial pollution control investments, respectively; while GFPZ policies have conflicting effects with CCCU and ETS in reducing carbon emissions and coal consumption, the GFPZ policy has conflicting effects with CCCU and ETS in reducing carbon emissions and controlling coal consumption. Finally, the study proposes a phased policy support system around carbon emission reduction in the power generation industry, energy structure transformation, and industrial environmental pollution control before 2030 and from 2030 to 2060.

Research on the spatiotemporal evolution and driving mechanism of coupling coordination between energy structure transformation and common prosperity

Promoting the transformation of energy structure is the important method to realize common prosperity in China. This paper estimates China's energy structure transition, explores the spatial evolution characteristics of the coupling and co-ordinated development of energy structure transformation and common prosperity, and analyzes its driving mechanism. The results show that the comprehensive evaluation index and coupling coordination degree of energy structure transformation and common prosperity show a steady improvement trend. The coupling coordination type is between low-degree and high-degree coordination. The coupling coordination degree presents a spatial allocation pattern of high in the east and low in the west, high in the center and low in the south. The transformation of energy structure and the drive of common prosperity are greatly affected by macroeconomics and policies. This study provides an empirical reference for promoting the transformation of energy structure and the realization of common prosperity.

Research on the impact of digital trade and energy consumption

<p>This study investigates the impact of the digital trade on energy consumption, as well as its mechanism, from 2014 to 2022 by developing a digital trade evaluation index system. We find that the growth of the digital trade can reduce per capital energy consumption and also passes various robustness tests. The main influencing mechanism is that the digital trade affects energy structure transformation and changes in final demand, which results in lower energy consumption. In terms of the spatial distribution, the digital trade decreases per capital energy consumption more in the eastern regions and promotes per capital energy consumption reduction less in the central regions, whereas there is no significant correlation in the western regions. The findings extend the benefits of the digital trade beyond economic and social welfare benefits and provide a consultation for digital economy for green development.</p>

Stable power supply system consisting of solar, wind and liquid carbon dioxide energy storage

Renewable energy is becoming the main subject of energy consumption with the accelerating transformation of energy structure. The renewable power supply systems sourced by wind and solar energies have attracted wide attention as they are of great significance to regions that are rich in renewable energy. In this study, the stable power system consisting of solar, wind and liquid carbon dioxide energy storage is proposed for the sake of meeting user electricity load. Thermodynamic and economic performance of the proposed systems with different application scenarios is analyzed and some interesting findings are summarized. The round trip efficiency and energy density of the liquid carbon dioxide energy storage system are 58.34 % and 23.41 kWh/m3, respectively. The start hour of dispatch can cause obvious influence on the energy storage capacity and there is an optimal dispatch start time to achieve the minimum energy storage capacity. The overall energy efficiency of energy storage-aided power system including solar and wind powers is much higher than that of the single sourced system. The energy efficiency of the solar-wind-LCES system is 94.61 % while it is only 80.31 % and 76.29 % for the wind-LCES and solar-LCES systems, respectively. The introduction of the liquid carbon dioxide energy storage into the renewable power supply system can greatly reduce the electricity purchasing investment.

Research on the air pollution reduction effect of winter clean heating policy

The international community is confronted with an urgent need to resolve the global climate crisis, which has emerged as a critical issue. China, in its capacity as a responsible major country, has proposed the “3060” goal and actively advocated for air pollution control. In northern China, a substantial quantity of coal is burned for heating in winter, leading to frequent air pollution, and seriously affecting people's health and quality of life. Clean heating is an important national livelihood strategy related to residents' heating and an essential manifestation of advancing ecological civilization construction. Based on panel data from 126 heating cities in the northern region from 2013 to 2020, this paper adopts the Difference-In-Difference (DID) model to investigate the effect and mechanism of the Winter Clean Heating Plan for Northern China on air pollution reduction. According to the research results, the policy has an abatement effect on northern region's air pollution emissions. The amount of air pollutant emissions has decreased by 17.3% since the policy's implementation. This policy has long-term effectiveness, which can become an effective measure for promoting air pollution reduction in the northern region. Secondly, economic factors, such as fiscal expenditure, and urban development factors, such as car ownership will have a driving effect on reducing air pollution, indicating that air pollution control is a systematic project that requires coordinated measures from all aspects. Thirdly, heterogeneity analysis indicates that the policy exerts a more substantial positive influence on air pollution control in Northwest China's cities and non-provincial capital cities. This indicates that cities should focus on implementing precise heating policies and not be “one size fits”. Finally, based on the theory of whole-process governance, this paper explores the indirect influence mechanism of the impact of the policy on air pollution reduction. By promoting energy structure transformation and promoting technological innovation, policy can indirectly improve the effectiveness of air pollution reduction. As an effective environmental regulation method, the policy can significantly reduce air pollution emissions in northern China, which is of great significance for the Chinese-style green modernization construction in this region.

Direct regeneration of cathode materials in spent lithium-ion batteries toward closed-loop recycling and sustainability

The transformation of energy structure is deemed as a paramount strategy in accomplishing the ambition of carbon neutrality. Lithium-ion batteries (LIBs), as one of the most exceptional energy storage and conversion devices available, play a pivotal role in this energy revolution. However, due to the extensive production and limited lifespan of LIBs, the retirements of LIBs are set to boom in the coming years. The proper and timely recycling of these batteries are of paramount importance, from both environmental and economic perspectives. Direct cathode regeneration technology is the most promising solution for the treatment of these waste cathodes, as it enables the healing of spent cathodes with minimal energy and chemical consumption, without compromising the original structure of the cathode. Herein, we analyzed the degraded mechanisms of spent LIBs and found that relithiation and defect reparation are crucial steps for the regeneration of spent cathode materials. Various direct regeneration methods previously reported have been summarized, and their respective advantages and limitations as well as technical challenges when implemented into practical industrial applications are discussed. In addition, possible solutions to these problems are proposed, which guide the future direction for the sustainable development of the battery recycling industry.

China can peak its energy-related CO2 emissions before 2030: Evidence from driving factors

China has pledged to achieve the CO2 emissions peak by 2030. This study aims to ascertain whether China can meet its commitment by predicting CO2 emissions. Based on industrial structure, energy structure, and energy intensity data forecasted by appropriate time series models, this study uses the Monte Carlo method to simulate the pathway of GDP growth rates and predict the trajectory of China's CO2 emissions from 2021 to 2035. The results reveal a 43.60% probability that China's CO2 emissions have peaked at 10.55 Gt in 2021. Furthermore, it is highly probable that China will achieve its CO2 emissions peak between 2023 and 2028. As the peak year shifts from 2023 to 2028, the mean value of CO2 emissions peak increases from 10.56 Gt to 10.71 Gt. Finally, the study employs the LMDI method to analyze the contributions of different driving factors to the CO2 emissions peak. The results indicate that energy structure transformation will be the primary factor driving the CO2 emissions peak, demonstrating the importance of transiting to a low-carbon energy system.

How does the transformation of the energy structure impact the coordinated development of economy and environment?

The energy structure transformation is of significant practical importance as it ensures energy security, accomplishes the "dual carbon" goal and realizes high-quality economic growth. In order to explore the impact exerted by energy structure transformation on the coordinated development of economic and environmental systems, this paper employs the coupled coordination degree model to measure the coupling degree of economic and environmental systems across 30 provinces in China from 2000 to 2021. Additionally, on the basis of theoretical analysis, it adopts the fixed effect model and the mediated effect model to provide a systematic explanation of the impact energy structure transformation exerts on the coordinated development of the economic and environmental systems, as well as the underlying mechanisms. The results reveal that China's structural transformation of energy consumption significantly promotes the coordinated development of the economic and environmental systems, a conclusion that remains robust even after consideration of the explanatory variable substitutions, municipality exclusion, and tail reduction. From the perspective of heterogeneity, regions with better economic development show a more obvious dividend effect of energy structural transformation on the coordinated development of the economy and the environmental system; energy structural transformation imposes a positive impact on the coordinated development of the economy and the environmental system only in regions characterized by high levels of human capital and urbanization. In terms of the mechanism of action, energy structural transformation can facilitate of industrial structure upgrading and then drive the coordinated development of economic and environmental systems. The study proposes several policy recommendations: transform the traditional fossil energy consumption mode, reduce the proportion of traditional fossil energy, introduce corresponding subsidy policies, encourage enterprises to invest in clean energy, boost investor confidence, and enhance employment quality and income level.

Can the digital economy promote urban green economic efficiency? Evidence from 273 cities in China

The development of the digital economy has changed human lifestyles and production and provided a new approach to achieving the United Nations Sustainable Development Goals (SDGs). As an important indicator reflecting both economic growth and ecological protection, the green economic efficiency (GEE) indicator is employed to express the level of sustainable development. By building an indicator system, introducing carbon dioxide emissions as an unexpected output and using a super-efficient slack-based measure (SBM) model, the the GEE of 273 cities in China are calculated. The development level of digital economy is calculated through principal component analysis (PCA). Unlike previous provincial-level studies, this study focuses on analyzing at the urban level. This study then uses a fixed effect model to analyze the effect of the digital economy on urban GEE. Based on various aspects, the transmission mechanisms of the digital economy on GEE have also been deeply analyzed. The results indicate that the digital economy has a positive effect on GEE. This conclusion is validated by endogeneity analysis and other robustness tests. The digital economy has a positive influence on urban GEE in Eastern, Central and Northeastern China. In large cities, medium-sized cities and cities with stricter governmental environmental regulations, the effect of the digital economy on GEE is more prominent. The mechanism analysis indicates that the digital economy mainly promotes urban GEE through the technological innovation effect, industrial structure optimization, energy structure transformation and market-oriented development. This study clarifies the role of the digital economy in advancing GEE and provides a reference to promote ecological development in developing countries.

The impacts of clean energy policies on air pollutants and CO2 emission reduction in Shaanxi, China

In response to environmental problems, China has implemented many policies to control its emission of air pollutants and CO2. As a significant source of pollutant emissions, energy use has received special attention. Shaanxi Province is a region of China with major thermal power generation, which consumes a large amount of fossil fuel and causes severe deterioration in ambient air quality. However, it is rich in natural resources that could support the development of solar energy, wind energy, and other renewable clean energies, making it a typical example of a region suitable for energy structure transformation. On the basis of environmental statistical data, field surveys, and data from the Shaanxi Provincial Bureau of Statistics, this study developed an inventory of anthropogenic source emissions of seven pollutants in 2017 in Shaanxi Province. In accordance with the established inventory, various scenarios were considered to analyze the impact of energy structure transformation on air pollutant emissions. In comparison with the Business-as-Usual scenario, the comprehensive clean energy use scenario reduced SO2, NOx, CO, PM10, PM2.5, VOCs, NH3 and CO2 emissions by 32.50%, 33.10%, 14.56%, 26.64%, 16.72%, 2.88%, 4.36% and 36.85%, respectively. Ambitious development of clean energy, such as wind and solar, could greatly reduce the emission of air pollutants, especially CO2, SO2 and NOx, that are derived mainly from fossil fuel combustion, showing that strict control of the energy structure could reduce pollutant emissions. This work is important for quantifying the impact of energy restructuring on regional air quality and providing pollution control policies for environmental managers.

Supply chain coordination mechanisms of coal power enterprises under renewable energy quota system: A perspective of game analysis

The renewable energy quota system has become an important policy tool for countries around the world to solve the differences in renewable energy resource endowments between regions and promote the transformation of energy structure. How to coordinate the supply chain of power generation enterprises from the micro level of enterprises has become a key issue to ensure the implementation of renewable energy quota system. By constructing a game analysis model, this research studied the coordination game problem between the supply chain of coal power enterprises and renewable energy enterprises, and compared and analyzed the differences in decision-making between centralized and decentralized situations. The results illustrate that in the case of centralized decision-making, although renewable energy enterprises and coal power enterprises can guarantee profits and carbon emission reduction effects. However, in the real situation of independent rational economic man, it is difficult to ensure the real realization of centralized decision-making. Further, the research proposed that in the case of decentralized decision-making, the negotiation mechanisms of revenue sharing, cost allocation, and revenue sharing + cost allocation were used to solve the supply chain coordination problem of renewable energy enterprises and coal power enterprises. The equilibrium solution of the game model under different negotiation mechanisms is obtained. Finally, the results of theoretical analysis were verified by practical examples and the corresponding sensitivity analysis is carried out. The conclusion has decision-making reference value for solving the coordination problem between coal power enterprises and renewable energy enterprises, improving the overall income of supply chain and carbon emission reduction, and effectively promoting the implementation of renewable energy quota system.

Multi-objective solution and decision-making framework for coordinating the short-term hydropeaking-navigation-production conflict of cascade hydropower reservoirs

The transformation of energy structure motivates hydropower to participate in peak shaving operations for grid stability, which conflicts with the multiple uses of cascade hydropower reservoirs. To coordinate the principal contradictory tasks of peak shaving, ship navigation, and power generation in day-ahead scheduling, a mixed integer linear programming model for the short-term multi-objective optimal scheduling is constructed. Specifically, a novel power release-based indicator is adopted to describe the navigation objective, while the minimization of the peak-valley difference of the residual load and the total water released are taken as the other two objective functions. Constraint aggregation and rectangular meshing methods are employed to handle the challenging nonlinear and nonconvex constraints. Subsequently, the Normalized Normal Constraint method, integrated with the mathematical optimization solver Gurobi, generates a set of well-distributed Pareto solutions, each representing a scheduling scheme. Finally, the Combined Weighting - Technique for Order Preference by Similarity to Ideal Solution is utilized as a decision-maker to trade off and determine a compromise solution for final implementation. Case studies on the cascade hydropower reservoirs of the Wujiang River in China demonstrate that the proposed model can adequately characterize the demands of various stakeholders, and the suggested framework can obtain an even and extensive Pareto front, mediate conflicts, and make reasonable decisions. Compared to the original peak-shaving scheme, the finalized compromise scheme reduces the peak-shaving effect by just 27.82% but offers simultaneous boosts of 96.54% in navigation benefits and 10.88% in power generation benefits. Consequently, the presented framework can be a promising alternative for conflict resolution of cascade hydropower reservoirs.

Towards a low-carbon economy: how does green credit affect carbon productivity?

As a financial instrument and a crucial component of the environmental governance system, the comprehensive impacts of green credit on both the economy and the environment remain unclear. This study examines Chinese provincial data from 2001 to 2018 and employs multiple models to assess the dynamic effects of green credit on carbon productivity. The findings indicate a significant positive influence of green credit on carbon productivity within local and surrounding areas. Furthermore, the promotion effect of green credit on carbon productivity is mainly through energy structure transformation, upgrading of industrial structure and green technology innovation. Interestingly, when considering the spatiotemporal aspect, we observe an initial marginal negative impact of green credit on carbon productivity, which subsequently transitions to a positive effect. The regions demonstrating the highest positive impacts of green credit are primarily concentrated in the southwestern region rich in renewable energy and the economically developed eastern coastal region.

What is the global causality among renewable energy consumption, financial development, and public health? New perspective of mineral energy substitution

Under the background of global warming and economic globalization, energy structure transformation and financial liberalization have become hot issues of global concern. Additionally, the replacement of renewable energy sources for mineral energy is placed great expectations to reduce environmental pollution and promote public health. Although the effects of renewable energy consumption (REC) and financial development (FD) on public health (PH) have been verified by researchers, the long-term causality among the three has not been explored, especially from global evidence. To verify the long-term relationship and causality among REC, FD, and PH at the global level, using annual panel data for 136 nations from 2000 to 2018, this paper employs the Cross-sectional dependence test, CADF unit root test, the second generation cointegration test, Pooled Mean Group estimation, and the Granger causality test. This paper finds some interesting results. First, the long-term co-integration relationship and the two-way causal relationship are among REC, FD, and PH. Second, REC and FD have a long-term promoting effect on PH, but have no significant effect in the short term. This conclusion holds up after a series of robustness tests. Third, there is heterogeneity in the long-term impact of REC and FD on PH. The long-term PH benefits of REC are more vital in low-polluting countries, trade-open countries, poor-institution countries, and non-emerging market countries, while FD has a long-term negative impact on PH in high-polluting and trade-tight countries. Based on the above results, we believe that it is necessary to formulate appropriate energy policies and financial policies according to local conditions. In summary, our results provide essential policy recommendations for energy transformation and public health improvement in countries around the world in the process of financial liberalization.