Optimization Of Energy Consumption Structure Research Articles

China's energy efficiency improvement considering renewable energy substitution: Applying a dynamic two-stage undesirable non-radial directional distance function

As the country with the largest CO2 emissions in the world, China is developing renewable energy as the main way to address climate change. By 2021, China's wind and solar power generation accounted for 40 % and 37 % of the global total, but there is an imbalance in the development of renewable energy within China. Different from existing research on energy efficiency evaluation that rarely considers renewable energy, this study constructs a dynamic two-stage undesirable non-radial directional distance function that divides traditional energy efficiency into electricity production efficiency (EPE) by considering renewable energy substitution effects and energy utilization efficiency (EUE) by considering changes in the energy consumption structure. Different from other empirical results, the western provinces, with advantages in renewable energy development, their EPE has significantly improved, and EUE has also improved with the optimization of energy consumption structure, thus their overall energy performance surpass that of the eastern and central regions. In addition, by comparing the room for improvement of variables, we find that most provinces can improve their energy performance by expanding the scale of renewable energy generation and increasing the proportion of electricity to total energy consumption. Therefore, we propose policy recommendations to promote the sustainable development of renewable energy.

The influence of carbon emission trading on the optimization of regional energy structure

The optimization of the energy structure is a crucial element in the development of green and low-carbon economies and societies. Market-based environmental regulations, such as carbon emissions trading, play a significant role in facilitating this transition. This study analyzes panel data from 30 provinces in China from 2007 to 2020. It empirically examines the impact and mechanism of carbon emissions trading pilot schemes on the transformation of energy consumption structure at the macro level, using the difference-in-differences method. The research findings indicate that provinces with carbon emissions trading pilots have experienced significant reductions in carbon emissions and carbon intensity, demonstrating clear emission reduction effects. Additionally, the transformation process of energy consumption structure has been notably accelerated, highlighting the correlation between initial carbon emissions trading and the regional energy utilization framework. Furthermore, in our extended mechanism analysis, we introduce two new variables - green finance and environmental regulation. Our analysis reveals that the level of green finance in carbon emissions trading pilot provinces significantly influences the degree of carbon emissions in these areas. Additionally, environmental regulation has a significant positive impact on the optimization of energy consumption structure.

Energy, economic, and environmental impacts of electricity market-oriented reform and the carbon emissions trading: A recursive dynamic CGE model in China

Electricity market-oriented reform and carbon emissions trading, as the main policies implemented in China's power sector, have a profound impact on China's green and low-carbon transition by promoting resource allocation efficiency and internalizing external environmental costs, respectively. Therefore, this paper constructed a dynamic recursive CGE model to measure the energy, economic, and environmental impacts of carbon emissions trading and electricity market-oriented reform from electricity market structure and pricing mechanism. The results show that the two policies have a synergistic effect on industrial structure optimization, energy consumption structure optimization, and carbon emission reduction. Specifically, the share of value-added of the tertiary sector, the growth rate of coal consumption, the share of thermal power consumption, and carbon emissions in 2030 are reduced by 5.70 %, 18.29 %, 2.55 %, and 2.838 trillion tons, respectively, compared with the scenario without carbon emissions trading and electricity market-oriented reform. However, imperfectly competitive market structures outperform perfectly competitive market structures in energy consumption structure and carbon emission reduction. Electricity price regulation is also more beneficial to GDP growth and increase in residential disposable income compared to price liberalization. To this end, returning emission trading scheme revenues to residents can effectively mitigate the adverse impacts caused by market-oriented reforms.

Source reduction and innovation: Can sustainable finance assist in mitigating haze pollution?

In the context of China's pursuit of an ecological civilization, controlling haze pollution (HP) and enhancing environmental quality occupy a pivotal role. Addressing this issue, this study utilizes a dataset spanning from 2006 to 2020, encompassing 278 Chinese cities, to examine the impact and mechanisms of sustainable finance on HP management. This research innovatively constructs a Sustainable Finance Index and employs fixed effects models, mediation effect models, and spatial Durbin models for comprehensive empirical analysis. The findings indicate a significant negative relationship between sustainable finance and HP, with pronounced effects in cities experiencing severe haze, cities in the central and eastern regions of China, and non-provincial boundary cities. Mechanism analysis reveals that sustainable finance curtails urban haze formation through the optimization of energy consumption structure, enhancement of energy efficiency, and advancement of environmental technologies. This is primarily achieved through pollution source reduction and innovation effects. Additionally, the study uncovers a spatial spillover effect of sustainable finance in mitigating HP, peaking within a 500-km radius. This research not only provides new insights into the role of sustainable finance in the construction of ecological civilization but also offers empirical support for policymakers and stakeholders in formulating clean production policies, enhancing both the academic dialogue and practical policymaking in environmental management and sustainable development.

Collaborative governance on industrial pollution and carbon emissions through synchronous development of factor markets: Impact and mechanism

Industrial sectors are pivotal areas for achieving the collaborative goal of pollution and carbon abatement, with technology playing a crucial role. Despite previous studies discussing the adverse environmental impacts of factor market distortion, there remains a research gap in examining the role of the technology market and the coordination among factor markets. This study introduces the concept of synchronous development between the capital and technology markets, drawing on the method of marriage-education matching in sociology. Furthermore, it employs the theoretical framework of new structural economics to investigate the impact and mechanisms of synchronous development between the capital and technology markets on the synergistic reduction of industrial pollution and carbon emissions, based on Chinese provincial-level panel data from 2000 to 2019 and auxiliary listed-company panel data. The results indicate that (1) the synchronous development between capital and technology markets facilitates collaborative governance in pollution mitigation and carbon abatement. (2) Industrial and technological structures serve as channel mechanisms, with the latter including technological innovation and productivity improvement of micro-enterprises as well as the optimization of energy consumption structure at the macro level. (3) Technology and labor quality endowments enhance the synergistic abatement effect, albeit by setting certain thresholds for actualization. (4) There is a reciprocal reinforcement and restrictive relationship between the synchronization and development of factor markets. This study applies the new structural economic theory to collaborative governance on pollution and carbon emissions, extending the research on the environmental and climate impacts of factor markets.

Have the pilot carbon markets achieved synergistic control of carbon abatement and pollution reduction? The quasi-experimental evidence from China

The Chinese government has emphasized the necessity of synergistic control for carbon abatement and pollution reduction in the protection of eco-environment, as part of the 14th Five-Year Plan and the Long-range Objectives Through the Year 2035. As an important tool to reduce CO2, the carbon market can also affect the air pollution synergistically. The study utilizes the multi-period difference-in-difference (DID) model to analyze the impact of carbon market on carbon abatement, as well as the synergistic effect on different air pollutants. The study analyzes the mechanisms for carbon market to achieve synergistic control from the perspectives of “quantity” and “category” comprehensively. The findings indicate that: (1) carbon markets can reduce CO2 significantly, with a synergistic effect mainly observed on SO2 and soot (dust). These results remain robust when focusing on the industrial sector or adopting the PSM-DID estimation, etc.; (2) the mechanisms to achieve synergistic control vary among different air pollutants. Promotion of technology can only synergistically reduce SO2. Optimization of energy consumption structure is the top priority for reducing CO2. The most effective mechanism to achieve synergistic control of air pollutants is improvement of energy utilization efficiency; (3) to achieve synergistic control goals, the Chinese national market should prioritize industries that release both CO2 and NOx in the rolling-out plan, enrich the trading tools, and formulate effective price signals.

Energy consumption structure model considering urban green and low-carbon transportation

<p class="Abstract">The importance of energy conservation and emission reduction has become the consensus of the international community, and Iraq is also actively improving the urban public transportation system to control carbon emissions. This paper collects panel data of Tikrit city in Iraq in the past 3 years, constructs a random effect variable coefficient model, and studies the impact of the development of urban low-carbon transportation system on the energy consumption structure. The study finds that the government can use public transportation pricing strategies to influence consumers. In order to realize the optimization of energy consumption structure, the impact of electric vehicles on energy consumption structure will decrease with the increase of urban development. The transportation sector can increase the purchase and travel costs of traditional cars by restricting travel, purchases, and charging parking fees, which affects the number of private cars and reduces the obstacles to optimizing the energy consumption structure. The government should increase financial subsidies, improve rail transit and reasonable bus (electric) vehicle operation systems, increase investment in new energy vehicle research and development, and encourage high energy density and low power consumption technologies. development, increase residents’ demand for new energy passenger vehicles, and optimize the energy consumption structure.</p>

Can green finance development abate carbon emissions: Evidence from China

Green finance has been treated as an important tool in the transformation process to low-carbon economy; however, it still remains a question whether the development of green finance could offer carbon savings, or inversely lead to more carbon debts. Based on panel data of 30 provincial administrative regions during 2008–2019, we use the fixed-effect model to examine the carbon emissions reduction effect of green finance. The empirical results suggest that green finance development exerts significantly negative influence on carbon emissions by energy consumption structure optimization and industrial structure upgrading. Besides, we also find that compared with green bond, green credit has a more pronounced carbon emissions reduction effect at present. Furthermore, the heterogeneity of green credit types and regional heterogeneity are both discussed in this study. It is indicated that the green credit oriented for energy conservation and environmental protection could restrain the carbon emissions more significantly while the green credit oriented for clean energy cannot contribute to cutting down carbon emissions as remarkably as other types of green credit. As for regional heterogeneity, results suggest that green finance could curtail carbon emissions in the central and western regions, while this effect is not significant for provinces in the eastern part of China. Thus, the green finance policies should be implemented based on regional characteristics in order to abate carbon emissions more effectively.

The Current Situation, Development, and Prospects of the Iron and Steel Industry in the Process towards the “Dual Carbon” Goals

The iron and steel industry is the largest carbon emitter in China’s manufacturing sector and one of the most important fields in the country’s response to climate change. This paper aims to explain the current situation, technological pathways, and future direction of green and low-carbon development of the iron and steel industry. According to the carbon emissions of the iron and steel industry, this paper analyzes the relationship between steelmaking technologies and carbon emissions, as well as the transformation trend of the world’s iron and steel industry, finding that China’s iron and steel industry faces both opportunities and challenges. Steel scrap recycling and electric furnace steelmaking technologies, re-electrification, hydrogen metallurgy, resource recycling and by-products, and carbon capture and utilization (CCU) are the main technologies tailored to the transformation pathways, and the optimization of energy consumption structure is an important direction for future development. Therefore, this paper believes that clean energy, as a guarantee for carbon mitigation, will play an increasingly important role in the process towards achieving carbon peaking and carbon neutrality goals (the “dual carbon” goals), in addition to the transformation of metallurgical technologies.

Research on the Influence Mechanism of Digital Economy on Energy Consumption Structure Under the Target of "Double-carbon"

Facing the increasingly severe resources and ecological problems, China has included the development of "green economy" in the development strategy. At present, China is experiencing a new round of energy reform with the dual effects of ecological and social. In order to solve the shortage of petrochemical resources and achieve the goal of "carbon reduction", the new round of energy conservation reform aims to increase the energy consumption of clean energy. Therefore, this study in the under the background of "double carbon" target, through the relevant research results at home and abroad, the energy industry development in China made a comprehensive analysis, qualitative analysis of energy consumption of green economy development mechanism, and adopt the entropy right Topsis model, space measurement model respectively in 2011-2021 our country provincial panel data empirical analysis, to explore the mechanism of energy consumption mechanism to promote the optimization of energy consumption structure in our country, realize the sustainable development.

Trajectory and drivers of China's consumption-based and production-based renewable energy consumption

China's renewable energy consumption was 6.37 EJ in 2018, making it the world's largest renewable energy consumer. Exploring the economic and social driving factors behind the dynamic evolution of renewable energy consumption in China not only serve China better development of renewable energy, but also has implications for other developing countries. Existing research was limited to apparent consumption based on static geographic boundaries, and ignored the embodied renewable energy consumption in trade, although China is the largest trade exporter and the second trade importer. This work extended the existing research to account production-based and consumption-based renewable energy consumption applying the multi-region input-output model and analyzed the embodied renewable energy flows in China's international trade. Furthermore, this paper adopted structural decomposition analysis to explore the driving factors of renewable energy production and consumption from consumption coefficient, production structure and final demand. The results show that, firstly, as the net embodied renewable energy importer, China's the renewable energy consumption on the production-based increased from 1.08 E+ 06 TJ to 6.79 E+ 06 TJ, and on the consumption-based increased from 1.08 E+ 06 TJ to 7.13 E+ 06 TJ. Secondly, major of embodied renewable energy came from China's trade with developed economies but the pattern of embodied renewable energy was undergoing change. Thirdly, the decomposition results showed that energy structure and final consumption were the leading drivers in China's renewable energy consumption growth. For further expansion of its renewable energy, policymaking should pay more attention on the adjustment and optimization of energy consumption structure and industrial structure to promote production side from sustainable consumption pattern.

Effect of Green Finance on Industrial Carbon Emissions in China——Empirical Analysis Based on Provincial Panel Data

Based on the Environmental Kuznets Curve (EKC), this paper empirically analyzes the impact of green finance development on industrial carbon emissions in China by using the panel data of Chinese mainland province. It is found that the development of green finance has significantly suppressed the industrial carbon emissions in China. Heterogeneity test shows that the inhibition effect on carbon emission in central China is the most obvious, and the inhibition effect on carbon emission in eastern and western regions decreases in turn. Technological progress significantly inhibits carbon emissions, especially in central China, followed by the western region and finally the eastern region. It is suggested to improve the green and low-carbon financing system, support the optimization of energy consumption structure and guide substantive technological progress, so as to promote the realization of carbon emission reduction targets.

The impact of carbon finance on energy consumption structure: evidence from China.

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.

Optimization path of green credit to energy consumption structure: A symbiotic development perspective of resource-based and non-resource-based industries

In the context of ecological environment construction, how to create a new development pattern in which environment and economy are coordinated has become an important goal of the Chinese government. From the perspective of the symbiotic development of resource-based industries and non-resource industries, this study discusses the path of green credit optimization of energy consumption structure by using the space Durbin model, based on the panel data from 30 Chinese provinces from 2006 to 2019. The study results are as follows: Both green credit and energy consumption structure have a significant positive spatial correlation. Furthermore, the energy consumption structure of local and adjacent areas is significantly optimized by green credit. Additionally, for non-resource-based regions, although green credit has no spatial spillover, it can significantly improve the local energy consumption structure, while green credit in resource-based regions significantly inhibits the optimization of the energy consumption structure in local and adjacent regions. Finally, from the perspective of the symbiotic development of resource-based industries and non-resource industries, although green credit can significantly improve the local energy consumption structure, it will inhibit the optimization of the energy consumption structure in adjacent areas. Therefore, government departments not only need to implement green credit policies according to local conditions but also actively guide exchanges and cooperation between resource-based industries and non-resource industries. This move promotes the symbiotic development of resource-based industries and non-resource industries and simultaneously improves the utilization efficiency of green credit, and optimizes the energy consumption structure.

Research Hotspots and Trend Analysis in the Field of Regional Economics and Carbon Emissions since the 21st Century: A Bibliometric Analysis

In recent years, the issue of regional economics and carbon emissions has become a research hotspot in the cross field of economy, environment and ecology. This paper selects the regional economics and carbon emissions related literature collected in the Web of Science (WOS) database as the basis, and uses the bibliometric software Citespace and VOSviewer to visually analyze the time distribution, organization, author and keywords in this research field. This paper provides a more systematic analysis of how different regions of China could achieve carbon emission objectives, from the aspects of regional industrial transformation, energy consumption structure, policy implementation and regional coordinated development. The keywords with high frequency are carbon emissions, economic growth and energy consumption, etc. The research hotspots can be divided into structural decomposition analysis, low-carbon industry transformation path, policy framework and energy efficiency, etc. The results show that future research should strengthen multidisciplinary cross-integration in different universities and institutions. However, based on in-depth analysis, the key factors which affect regional carbon emissions are regional policy implementation, changes in industrial structures, optimization of energy consumption structure and carbon trade market mechanism. Finally, we suggest that institutions and scholars should conduct adequate interdisciplinary and cross-industry cooperation; industrial sector development should consider local endowment; there should greater use of clean energy to optimize the energy consumption structure; and an increase in R&D carbon capture and sequestration technology.

How Energy Price Distortions Affect China’s Economic Growth and Carbon Emissions

China’s energy market reform is characterized by “asymmetry” as a result of the transition from a planned economy to a market economy, leading to typical distortions in energy prices. Using panel data from 30 Chinese provinces during 2006–2018, this paper examines the impact of the price distortions of fossil energy sources (coal, oil, and natural gas) as well as renewable energy on China’s economic growth and carbon emissions. The results show that coal price distortion is the highest among the fossil energy sources, followed by oil and natural gas. Renewable energy price is positively distorted. Not all price distortions of energy sources significantly impede economic growth—only those of coal and renewable energy. In contrast, oil and natural gas price distortions promote economic growth. All four energy price distortions contribute significantly to the increase in carbon emissions. Further analysis reveals that regional heterogeneity exists in the impact of energy price distortions on economic growth and carbon emissions. Additionally, this study finds that technological innovation, industrial structure upgrading, the investment effect, the optimization of energy consumption structure, and environmental regulations are important transmission mechanisms of energy price distortions affecting China’s economic growth and carbon emissions. The findings of this study can help us to understand the relationship between energy price distortions and China’s economic growth and carbon emissions, and provide a reference for formulating energy price reform policies that benefit the win-win development of China’s economy and environment.

Optimization of energy consumption structure based on carbon emission reduction target: A case study in Shandong Province, China

It is urgent to significantly reduce greenhouse gas emissions to actively deal with global warming. This paper investigates Shandong Province, a typical province of energy consumption, as the research object, aiming to optimize total energy consumption and consumption structure in the future planning year. This paper constructs a methodological system to optimize energy consumption structure in Shandong Province, using a scenario combination of system dynamics (SD) prediction and analysis based on the coupling of key scenario elements affecting different energy consumption from different perspectives. Structural equation modeling and SD sensitivity analysis indicate an overlap between key factors restricting energy consumption. Pairing the key scenario factors can better reflect the internal mechanism of energy consumption development. Based on this, 21 scenarios based on different combinations of the key elements are constructed. Through SD prediction and analysis, the most suitable scenario mode for optimizing energy consumption structure in Shandong Province is selected. This paper provides a suitable development range for the average gross domestic product growth rate, the proportion of secondary industry, energy consumption intensity of secondary industry, and the urbanization rate for Shandong Province. This paper can provide a reference for similar research and the government in formulating the optimization scheme of energy consumption structure.

Energy-related carbon emissions and structural emissions reduction of China's construction industry: the perspective of input-output analysis.

Excessive carbon emissions from energy consumption seriously restrict China's sustainable development and eco-environmental protection. Although the carbon emissions from the construction industry are less than that of the power, transportation, and manufacturing sectors, the carbon emissions released by the construction industry cannot be ignored due to its extensive development trend of high energy consumption and low efficiency. Based on this, this paper studies energy-related carbon emissions and emissions reduction of China's construction industry from 2007 to 2017 by adopting the input-output analysis method, energy consumption method, and structural decomposition model. The results show that within the sample range: (1) The optimization of the construction industry energy consumption structure has a significant reduction effect on the growth of energy carbon emissions from the construction industry in China, and the reduction effect has shown an increasing trend over time. However, it should be noted that in this sample range, the optimization of energy consumption structure in the construction industry is mainly reflected in the decrease of the proportion of high-carbon energy consumption such as raw coal, while low-carbon energy such as natural gas has not played a significant role. Therefore, the future energy optimization space of China's construction industry is still huge. (2) Energy intensity effect and input structure effect have a positive inhibitory effect on carbon emission growth of the construction industry, and the inhibitory effect of energy intensity effect is stronger than that of input structure effect. It shows that in the sample range, the generalized technological progress and energy efficiency of the construction industry have been better optimized and improved. (3) Except for 2015-2017, the final demand effect in other intervals has a positive effect on the growth of carbon emissions in the construction industry, and the secondary and tertiary industries play a major role in the final demand effect. It shows that the total demand for the construction industry in various industries still maintains a growth trend. This paper provides a theoretical analysis basis and practical guidance for China's construction industry to carry out more accurate and efficient emission reduction from the supply-side energy varieties and demand-side industry level, and further enriches the existing research on carbon emissions of the construction industry from the perspective of input-output analysis.

Towards the environmentally friendly manufacturing industry–the role of infrastructure

Infrastructure development and the green transition of manufacturing are two crucial issues concerning the national economy and people's livelihood. However, not many literatures discuss the influencing mechanism connecting the two. This paper starts from a new research perspective of infrastructure development and explores the potential ways to improve manufacturing's ETFP. The empirical results indicate that the infrastructure development has indeed improved the green development level (GDL) of manufacturing. This impact is heterogeneous in terms of different infrastructure types and planning periods. Besides, the completed infrastructure helps the formation of an environmentally friendly development model, while the new infrastructure investment could generate negative environmental externalities. Through mechanism analysis, we found that infrastructure mainly promotes the GDL through the two tracks: scale effect and energy structure adjustment. The technological progress and industrial structure adjustment did not play the expected mediating impact. The dynamic panel threshold model results proved that with the expansion of the scale effect and the optimization of energy consumption structure, the role of infrastructure in promoting the manufacturing's GDL could be stronger. Some policy recommendations are proposed to provide a reference for the infrastructure programming and the green transformation in the manufacturing industry.

The impact of energy consumption structure on China’s carbon emissions: Taking the Shannon–Wiener index as a new indicator

After several years of steady decline, carbon emissions began to rise in 2017. If this trend is not curbed as soon as possible, the efforts made for carbon emission reduction will be wasted. Although the effect that the energy consumption structure brought to carbon emissions has been studied in pieces of literature, the limit is that they all take the ratio of coal consumption (CS) as the index of energy consumption structure. With the optimization of energy consumption structure, the index they use is no longer convincing. Shannon–Wiener diversity index (SWI) is an index used to investigate the diversity within the local flora of a plant community, and in this paper, it is innovatively used to reflect the structure of the energy consumption. To test the superiority of the new index in the study of carbon emissions, the Autoregressive Distribution Lag model (ARDL) was used, and we find out the effect of Gross Domestic Product (GDP), Urbanization Rate (UR), Trade Structure (TS) and energy consumption structure on carbon emissions in China through the data from 1985 to 2016. The results show:(1) the R2 of the carbon emission model constructed by SWI is as high as 0.9938, which means the model is stable;(2)During the research period, we found the relationship between the environmental quality and the squared term of GDP per capita is a U-shaped curve, so the Environment Kuznets Curve (EKC) hypothesis is not applicable in China;(3)The results also show that the inflexion point of the U-shaped curve is delayed;(4) Urban development and the promotion of trade structure will bring the increase of carbon emissions, while the optimization of energy consumption structure will slow it down. This paper will provide new ideas for studying the impact of energy consumption structure on carbon emissions, and put forward policy suggestions.