CO2 Emissions In China Research Articles

Tourism energy consumption estimation and driving factors of carbon emissions based on LMDI and panel data models

Tourism has had some negative effects while generating positive results. The carbon emissions produced by tourism, which is not a “smokeless industry” in traditional cognition, account for a certain proportion of the global greenhouse gas emissions. Tourism transportation, tourist accommodation, and other tourism activities all contribute to the carbon emission of tourism, and various tourism activities not only stimulate the economy but also increase air pollution. As a big industry, tourism’s growth and development have continuously increased energy consumption, and the pressure on energy conservation and emission reduction has also been greatly aggravated. In this study, the tourism carbon emissions in each province of China were estimated using a “top-down” calculation model, the tourism energy consumption factors were decomposed using a logarithmic mean Divisia index model, and the driving factors of tourism carbon emissions were analyzed through a panel data model. Results show that the tourism carbon emissions in China rapidly increased from 360.74 million tons in 2006 to 853.28 million tons in 2021. The driving factors of tourism energy consumption in China are economic development, energy efficiency, and population, while the inhibiting factors are tourism intensity and energy structure. The per capita GDP, the proportion of the tertiary industry, the turnover of tourists, and the level of urbanization all significantly promote the growth of tourism carbon emissions in China at 1%. The research results are of great significance to the proposal of measures for tourism carbon emission reduction in combination with the situation of various provinces and cities, promoting regional economic development and boosting the development of tourism in China under the background of a low-carbon economy.

Defining provincial responsibility for controlling transportation CO2 emissions in China: As fairness perspective

Transportation CO2 emissions (TCE) in China account for a high proportion and are growing rapidly, making this sector likely one of the last to achieve carbon peaking nationally. However, directly comparing absolute TCE values to measure the responsibility of TCE control targets for each province in future years would be unfair due to substantial disparities between provinces in population, affluence, and technology characteristics. To address this issue, this study establishes an equitable and efficient framework to help policymakers determine province-specific and year-specific TCE benchmark and policy values. The results show that the less developed regions face greater challenges in controlling TCE per unit of GDP, and they should focus more on the use of shifting and improvement measures to reduce TCE. In contrast, the developed provinces bear a higher responsibility for TCE control in the near future; thereby, they need to implement an appropriate combination of measures.

Synergetic effect evaluation of pollution and carbon emissions in an industrial park: An environmental impact perspective

IntroductionHow to achieve synergistic control of pollution and carbon emissions has become a global concern. This article focuses on an industrial park and aims to evaluate the synergistic effect of pollution and carbon emissions from an environmental impact perspective. We propose a synergistic effect evaluation method based on life cycle assessment (LCA-SE method). The synergistic effect index (Els) indicates that the industrial park exhibits a strong synergistic effect in reducing pollution and carbon emissions. Based on our findings, we draw the following conclusions: First, carbon emissions should be given priority in emissions control. Second, photovoltaic power generation and energy conservation measures can effectively achieve synergistic efficiency in reducing pollution and carbon emissions. Third, when considering synergistic control of pollution and carbon emissions, priority should be given to pollutant reduction measures that can simultaneously reduce energy consumption during the process. This study presents a novel approach, the LCA-SE method, to assessing the synergistic impact of pollution and carbon emissions, offering valuable insights into the coordinated management of pollution and carbon emissions in China.

Coordinated reduction effect of pollutant discharge fees on enterprises' pollutant and carbon emissions in China

With the aggravation of global climate change and environmental pollution, governments of various countries have taken measures to promote sustainable development. This study evaluates the influence of China's pollutant discharge fees (PFE) on the enterprises' coordinated emissions reduction of pollutant and carbon based on fixed effects model by using a broad sample of 138,371 observations during 2003–2009 derived from two microenterprise datasets and a city dataset. Based on the empirical results, the rising price of PFE will lead to coordinated emissions reduction, specifically, a 1% increase in PFE leads to 0.0835% reduction in SO2 and 0.0294% decrease in CO2. Through heterogeneous analysis, this study finds that PFE heterogeneously influences pollutant and carbon emissions. The collaborative emissions reduction effects of PFE are significant in low pollution intensity regions, high energy consumption intensity regions, and state-owned enterprises. Furthermore, this study concludes that the clean energy substitution effect is an essential mediation mechanism of the impact of PFE on coordinated emissions reduction, while the energy-saving effect is not significant. This study provides several policy implications for achieving the goal of coordinated decreasing the emissions of carbon and pollutant from the perspective of PFE.

Investigating the driving factors of carbon emissions in China's transportation industry from a structural adjustment perspective

Promoting the transport industry to achieve a carbon peak and controlling carbon emissions in various regions of China through structural adjustment are important means to significantly reduce CO2 emissions. To explore the drivers of carbon emissions from China's transportation sector from 2006 to 2021. And constructs the IPAT-S (IPAT model considering structural adjustment) model, the structural equation is combined to explore the carbon emission reduction path of China's transportation industry from the perspective of structural adjustment. The results show that the structural adjustment is beneficial to alleviate the pressure of emission reduction, carbon emissions from the national transportation sector show a pattern of “low in the north and high in the south”, with the trend gradually shifting to the central region, and the spatial structural effect on carbon emissions has been significantly strengthened, the industrial structure, energy structure and transportation structure still contribute to the carbon emissions of the transportation industry. From the regional level, there are some differences in the impact of structural adjustment on carbon emission reduction in different regions, but optimizing the energy structure will be conducive to carbon emission reduction. In the case of the Northeast region, the energy consumption structure, industrial structure, and transportation structure do not inhibit carbon emissions, and the structural emission reduction in the Central region has begun to bear fruit. The structural adjustment in the eastern and western regions has yet to be improved, which will also provide the government with policy recommendations for structural emission reduction based on regional differentiation.

Revisiting urban environmental Kuznets curve hypothesis: evidence from carbon emissions in China’s prefecture-level and above cities

Revisiting urban environmental Kuznets curve hypothesis: evidence from carbon emissions in China’s prefecture-level and above cities

Bigger cities and less carbon? Government-driven urbanization and carbon emissions in China

The urbanization mode plays a crucial role in urban energy transformation and greenhouse gas emissions. However, the existing research on how government-driven urbanization (GDU) influences urban carbon emissions is relatively insufficient. By combining satellite imagery data and socio-economic data between 1999 and 2021, this research exploits China's city-county mergers (CCM) as a quasi-experiment trial to investigate the impact of GDU on carbon emissions based on the staggered difference-in-differences (DID) approach. This study indicates that GDU results in a 1.8% decrease in carbon emission intensity. The mechanism analysis shows that GDU reduces carbon emission intensity through population agglomeration, intensive land use, and industrial structure adjustment. Heterogeneity analysis shows that GDU's policy effect is influenced by the county's geographical location and socio-economic characteristics. The reform influence is more compelling in counties located on the administrative boundary, with less financial pressure or a better industrial foundation. In the future, policymakers need to nudge for urbanization appropriately according to specific scenarios and promote urban energy transition and carbon reduction.

Research on the Impact of Digital Trade on Urban Carbon Emissions in China under the "Dual Carbon" Target

After the "dual carbon" goal was put forward, low-carbon development has gradually become the focus of attention from all walks of life, and digital technology plays an important role in the process of helping carbon emission reduction. Digital trade, as an active field in international economy and trade, is of great significance to the economic growth of all countries and to deal with the problem of carbon emission reduction. This paper analyzes the transmission path of digital trade on urban carbon emission reduction in China from the theory of scale effect, structure effect and technological progress effect, and based on the panel data of 280 cities in China from 2011 to 2019, uses two-way fixed effect model to conduct regression analysis on the carbon emission reduction effect of digital trade. The study finds that China's digital trade development reduces urban carbon emission intensity, and the conclusion is still valid after the robustness test. Heterogeneity analyses show that the carbon emission reduction effect of digital trade varies in different regions in the East, West and Centre, as well as in regions with different degrees of carbon emissions. In terms of the transmission path, digital trade reduces regional carbon emission intensity by promoting scale effects, technological progress and industrial structure upgrading. Therefore, on the road of actively realizing the goal of "dual carbon", China should vigorously promote the development of international trade mode mainly represented by digital trade. At the same time, we fully recognize the heterogeneity of the impact of digital trade on carbon emissions, and adopt differentiated policies according to the different utility levels of digital trade on carbon emissions in different regions. This will narrow the "digital divide" between cities and help achieve China's "dual carbon" goal.

Decomposition analysis of regional differences in China's carbon emissions based on socio-economic factors

Developing policies and setting carbon reduction targets for various regions in China are important actions to narrow the gap of regional carbon emissions. This study reports on the differences in carbon emissions in the eastern, central, and western regions of China from 2005 to 2021 using the Theil index, and decomposes carbon emissions into emission intensity, industrial structure, economic scale, and population size effects using the Logarithmic Mean Divisia Index. In order to analyze the impact of socio-economic factors on carbon emissions, the industrial structure and emission intensity effects are divided into six socio-economic sectors. The major outcomes reported that: (1) the regional differences account for 70 % of the total carbon emissions difference, and the eastern region reported the most significant carbon emission difference; (2) the emission intensity and the economy scale are the top two effects on carbon emissions. The economic scale effect always drives an increase in carbon emissions, while emission intensity promotes a decrease in carbon emissions. The industrial structure effect shows a gradually decreasing trend in all regions, especially in the eastern region, the effect has turned negative since 2013. This is due to the proposed industrial transformation and upgrading in China since 2013, which has promoted the reconstruction of competitive advantages for high polluting heavy industry enterprises and accelerating the green transformation of industrial technology; (3) the industry sector contributes to the highest carbon emissions, followed by the transportation sector. Both sectors are the top two emitters and should be targeted for carbon reduction. The carbon emissions were generated based on the terminal energy consumption. The contribution effects of multiple industries and the differences in carbon emissions as affected by the driving factors and economic mechanisms among different regions in China were analyzed.

Integrating solar electricity into a fossil fueled system

The power sector is a major contributor to carbon emissions in China, accounting for nearly half of all emissions, and therefore emission reductions from this sector will be critical, if China is to meet its 2060 targets. Deploying renewable energy sources is the most promising approach to decarbonizing the power sector. However, the intermittency and non-dispatchable nature of wind and solar power pose significant challenges to grid stability, particularly when these sources reach high penetration rates. During China's ongoing energy transition, coal-fired power units will be used to meet peak loads when solar and wind generation is not available. The economic and environmental implications of such a scenario are unclear. In light of this uncertainty, this study applies a unit commitment model to investigate the economic and environmental performance of load shaving strategies across different scenarios. Results show that, in the absence of energy storage systems, a solar penetration rate of 40 % will create an economic bottleneck, and high solar penetration would even increase the total carbon emissions of the whole power system. Moreover, the power system would choose to cycle the large thermal units first to accommodate the solar power, and start-stop strategy is subordinate.

How does the digital transformation of agriculture affect carbon emissions? Evidence from China’s provincial panel data

Agriculture is becoming a substantial contributor to carbon emissions in China, and the efficient reduction of agricultural carbon emissions (ACEs) has become a universal concern. Currently, the digital transformation of agriculture (DTA) provides a new way to reduce carbon emissions. However, questions regarding whether and how DTA suppresses ACEs remain the focus of both academic and practical attention; thus, they serve as the objectives of this study. Based on theoretical analyzes, the carbon emission reduction effect of DTA is empirically analyzed using panel data from 30 Chinese provinces between 2015 and 2021 with a benchmark regression model, mediating effect model and threshold effect model. The results show the following: (1) DTA significantly reduces ACEs. (2) DTA reduces ACEs through three paths: expanding the agricultural production scale, optimizing the agricultural industrial structure, and promoting agricultural technological progress. The agricultural industrial structure has the most considerable mediating effect, while the agricultural production scale expansion has the smallest effect. (3) The inhibitory effect of DTA on ACEs shows very distinct heterogeneity. DTA primarily reduces ACEs in eastern and nongrain production areas yet has an insignificant impact on other areas. In addition, the DTA has a significant inhibitory effect on ACEs from both fertilizers and diesel oil. (4) The inhibitory effect of DTA on ACEs is nonlinear rather than linear. There is a single threshold effect for the effect of DTA on ACEs, which is insignificant below the threshold and significantly negative above the threshold. Therefore, China’s central and local governments need to increase the level of DTA, encourage farmers to moderately expand the scale of their operations, emphasize the agricultural service industry, and enhance agricultural technological innovation to ultimately reduce ACEs.

Industry star or production elite: evidence from total factor productivity of Chinese electricity sector's green transformation.

China is constantly seeking rapid, high-quality growth in order to meet its carbon peaking and neutrality goals. Approximately 40% of China's carbon emissions come from the electric power industry, which is beset by issues of poor efficiency and excessive emissions. Thus, it is essential to determine if environmental restrictions increase economic benefits total factor productivity while still preserving the environment. We use the Quasi-DID method to examine the impact of carbon emissions trading scheme on firm-level total factor productivity of electric power companies. The findings demonstrate the following: (1) carbon emissions trading scheme considerably impedes total factor productivity development; (2) the primary cause of this detrimental impact is the need for additional improvements in marketization since green innovation is still in its infancy; (3) additional study indicates that law enforcement's heterogeneity is what affects this restriction. Our research may both enhance the Chinese carbon emissions trading scheme's effectiveness assessment framework and point out several potential avenues for high-quality growth.

Impact of urban compactness on carbon emission in Chinese cities: From moderating effects of industrial diversity and job-housing imbalances

In the context of sustainable urban space utilization and carbon neutrality, this study systematically explores the relationship between urban form and carbon emissions in China from 2005 to 2020. Utilized night-light and Open-source Data Inventory for Anthropogenic CO2 data from 260 cities to measure urban form and carbon emissions, the threshold effect of urban form on carbon emissions was identified, and the moderating effects of industrial diversity and job-housing imbalances were explored. The results of the study show that, firstly, as urban form becomes compact, carbon emissions within built-up areas and cities both show a trend of decreasing and then increasing. In small and medium-sized cities, urban compactness tends to reduce carbon emissions, while in large and mega-cities, a more compact urban form increases carbon emissions. In addition, in cities with high industrial diversity and low job-housing imbalances, a more compact urban form helps to reduce carbon emissions. To optimize the carbon reduction benefits of urban compactness, our study offers urban planners’ insights for comprehensive planning that integrates urban form with both production and residential considerations.

How Can Financial Innovation Curb Carbon Emissions in China? Exploring the Mediating Role of Industrial Structure Upgrading from a Spatial Perspective

How Can Financial Innovation Curb Carbon Emissions in China? Exploring the Mediating Role of Industrial Structure Upgrading from a Spatial Perspective

The role of financial innovation in carbon intensity reduction: perspectives from energy structure transition and fiscal policies.

Carbon emissions are important factors causing global warming, which requires global efforts to deal with. In this paper, we investigate the mechanism of financial innovation on reducing carbon emissions in China by constructing a financial innovation development index with factors of green finance as well as fintech development. Empirical results show that financial innovation contributes to reduce carbon intensity by promoting energy structure transition as well as public fiscal expenditure on energy conservation and environmental protection. Moreover, heterogeneity exists in the effect of financial innovation on carbon emission reduction. Financial innovation has a significant role in reducing carbon intensity in eastern regions, but has a relatively small influence on central and western regions. Furthermore, financial innovation has a lag effect on reducing carbon intensity.

The North-South industrial transfer of manufacturing and the pattern of carbon emissions in China

In recent years, the gap between the north and the south of China has been expanding, showing a decreasing proportion of value-added and an increasing proportion of carbon emissions in the north of China, and vice versa in the south of China. Based on the most recent inter-provincial input-output table of China in 2012 and 2017, this paper focused on the North-South industrial transfer of manufacturing, quantified its impact on regional carbon emissions, and decomposed the path of impacts. The results suggest that the North-South industrial transfers of China during 2012-2017 indeed aggravated the imbalance of carbon emissions in the north and the south of China. Further explorations of path decompositions show that the spillover effect through production linkages is the major path where industrial transfer influences regional carbon emissions, particularly in the north of China. The results provide insightful policy implications for the achievement of carbon emissions reduction targets in China as well as the globe.

The Impact of the Digital Economy on Provincial Carbon Emissions in China

The Impact of the Digital Economy on Provincial Carbon Emissions in China

Agricultural Carbon Emissions in China: Estimation, Influencing Factors, and Projection of Peak Emissions

Agricultural Carbon Emissions in China: Estimation, Influencing Factors, and Projection of Peak Emissions

Prediction analysis of carbon emission in China's electricity industry based on the dual carbon background.

The electric power sector is the primary contributor to carbon emissions in China. Considering the context of dual carbon goals, this paper examines carbon emissions within China's electricity sector. The research utilizes the LMDI approach for methodological rigor. The results show that the cumulative contribution of economies scale, power consumption factors and energy structure are 114.91%, 85.17% and 0.94%, which contribute to the increase of carbon emissions, the cumulative contribution of power generation efficiency and ratio of power dissipation to generation factor are -19.15% and -0.01%, which promotes the carbon reduction. The decomposition analysis highlights the significant influence of economic scale on carbon emissions in the electricity industry, among the seven factors investigated. Meanwhile, STIRPAT model, Logistic model and GM(1,1) model are used to predict carbon emissions, the average relative error between actual carbon emissions and the predicted values are 0.23%, 8.72% and 7.05%, which indicates that STIRPAT model is more suitable for medium- to long-term predictions. Based on these findings, the paper proposes practical suggestions to reduce carbon emissions and achieve the dual carbon goals of the power industry.

Study on Spatial-Temporal Disparities and Factors Influencing Electricity Consumption Carbon Emissions in China

Investigating the factors influencing the spatial-temporal disparities in China’s electricity consumption carbon emissions (ECCEs) will be of great help to advancing the reduction in carbon emissions on the consumption side of electricity. Based on the measurement of the ECCEs in 30 Chinese provinces between 2005 and 2021, we utilized the natural breakpoint method and the Dagum Gini coefficient to analyze the spatial-temporal disparities in ECCEs at the provincial and regional levels, and then we used Geodetector to explore the factors influencing the spatial-temporal disparities in ECCEs. The results revealed the following: (1) There were obvious inter-provincial spatial disparities in ECCEs, with coastal provinces such as Jiangsu and Guangdong consistently ranking at the top of the country and inland provinces such as Qinghai and Yunnan having relatively low carbon emission values. (2) The overall disparities in China’s ECCEs fluctuated and rose, with inter-regional disparities being the primary source of the overall disparities. (3) Economic development, industrialization level, population density, and foreign direct investment all had strong explanations for the spatial-temporal disparities in China’s ECCEs. When all these influencing factors were spatially superimposed, their effects were enhanced.