Provincial Carbon Research Articles

What determines provincial carbon emission reduction performance in China? A study on co-movement effect based on QCA

What determines provincial carbon emission reduction performance in China? A study on co-movement effect based on QCA

Study on provincial carbon emission inequality in China from 1995 to 2019 based on the improved Gini index

The Chinese government has set ambitious carbon peak and carbon neutrality goals for 2030 and 2060. To achieve these targets, China will need to adopt stricter carbon emission policies in the future. Due to China’s vast territory, there are significant disparities in economic development levels and carbon dioxide emissions (CEs) among its provinces. Therefore, equitable carbon reduction policies are crucial for regional economic development. This study calculates CEs from energy consumption in 30 Chinese provinces using energy balance tables and CEs factors. Based on this, the Dagum decomposition Gini index is used to quantitatively assess CEs inequality between the primary, secondary, and tertiary industries in China’s central, eastern, and western regions. The results show that over the past 25 years, China’s CEs have increased from 3.17 billion tons to 13.32 billion tons, with an average annual growth rate of 6.17%. Additionally, CEs inequality in China has decreased by 3.96%. Moreover, CEs inequality in the eastern provinces has decreased the most (57.65%), followed by the central and western regions. Furthermore, CEs inequality in the secondary industry has expanded in all three regions, while inequality in the tertiary industry remained smaller due to technological and geographical constraints.

Natural gas and the battle of carbon emissions: Interpreting the spatial effects of provincial carbon emissions in China

Natural gas and the battle of carbon emissions: Interpreting the spatial effects of provincial carbon emissions in China

Drivers and Mechanisms of Provincial Carbon Emission Reduction in China: A General Equilibrium Analysis

Drivers and Mechanisms of Provincial Carbon Emission Reduction in China: A General Equilibrium Analysis

Estimation of national and provincial carbon emissions, terrestrial carbon sinks and their relative contribution to emission reductions during 1980~2020

Estimation of national and provincial carbon emissions, terrestrial carbon sinks and their relative contribution to emission reductions during 1980~2020

Dynamic Multi-Factor Correlation Analysis for Prediction of Provincial Carbon Emissions in China’s Bohai Rim Region

This study presents a dynamic multi-factor correlation analysis method designed to predict provincial carbon dioxide emissions (CDE) within China’s Bohai Rim region, including Tianjin, Hebei, Shandong, and Liaoning. By employing the sliding window technique, dynamic correlation curves are computed between various influencing factors and CDE at different time intervals, thereby facilitating the identification of key feature attributes. A novel metric, the Consistency Index of Influencing Factors (CIIF), is introduced to evaluate the consistency of these factors across regions. Furthermore, the Accurate Predictive Capability Indicator (APCI) is defined to measure the impact of different feature categories on the prediction accuracy. The findings reveal that models relying on a single influencing factor exhibit limited accuracy, whereas combining multiple factors with diverse correlation features significantly improves the prediction accuracy. This study introduces a refined analytical framework and a comprehensive indicator system for CDE prediction. It enhances the understanding of the complex factors that influence CDE and provides a scientific rationale for implementing effective emission reduction strategies.

The Impact of Digital Finance on Provincial Carbon Productivity: Empirical Evidence from China

Based on the provincial panel data from China, this study explores the impact of digital finance on provincial carbon productivity. Further, the regional heterogeneity and spatial spillover effect, the moderating effects of financial supervision and environmental decentralization, and the mediating effect of green technology innovation are analyzed. The results show that digital finance can significantly improve provincial carbon productivity, and clearly promote carbon productivity in the underdeveloped provinces (i.e., central and western regions), but not in the economically developed provinces (i.e., eastern region). Digital finance has a positive spatial spillover effect on carbon productivity. In addition, financial supervision and environmental decentralization play moderating effects in the impact of digital finance on carbon productivity. Green technology innovation plays a partial mediating effect in the impact of digital finance on carbon productivity. This study provides a reference for improving carbon productivity and developing a low-carbon economy.

Research on provincial implied carbon emissions in China under the shared responsibility driven by new quality productivity: A new approach

Research on provincial implied carbon emissions in China under the shared responsibility driven by new quality productivity: A new approach

Geographic matching analysis between green finance development and carbon emissions in China’s new era of environmental transition

Geographic matching analysis between green finance development and carbon emissions in China’s new era of environmental transition

Multi-step carbon emissions forecasting using an interpretable framework of new data preprocessing techniques and improved grey multivariable convolution model

Multi-step carbon emissions forecasting using an interpretable framework of new data preprocessing techniques and improved grey multivariable convolution model

Provincial equity and enhanced health are key drivers for China's 2060 carbon neutrality

Provincial equity and enhanced health are key drivers for China's 2060 carbon neutrality

Do Tradable Green Certificates Promote Regional Carbon Emissions Reduction for Sustainable Development? Evidence from China

The tradable green certificate (TGC) scheme is an important approach for mitigating carbon emissions within the context of a renewable energy development strategy and regional sustainable development. However, studies investigating the role of TGCs in encouraging carbon emissions reduction in China are limited and inconclusive due to ignoring the interference of other renewable energy policies and little distinguishing the impact of different green certificates. Using Chinese provincial data from 2013 to 2023, this study employs a difference-in-differences strategy to estimate the effect of the TGC policy on regional carbon emissions. The results reveal that the TGC policy significantly reduces provincial carbon emissions, and this reduction is predominantly contributed by certificate-electricity integration green certificates rather than certificate-electricity separation certificates. A 1% increase in the provincial trade volume of certificate-electricity integration green certificates can reduce total provincial carbon emissions by 0.8–1.3%. These findings hold across a series of rigorous robustness tests. This study also explains the different effects between certificate-electricity integration and certificate-electricity separation green certificates by the concept of additionality. To effectively reduce carbon emissions in the future, the TGC system must meet the requirement of additionality. These insights can provide reference for the improvement of TGC policy to better achieve the carbon reduction objective and sustainable development.

Institutional Performance and Carbon Reduction Effect of High-Quality Development of New Energy: China’s Experience and Policy Implication

Based on the policy text from 1999 to 2022, this paper quantitatively analyzes photovoltaic power, wind power and new energy policies in mainland China by keyword capture and policy strength and establishes a spatial Durbin model to study the carbon reduction effects. The results show the following: (1) The development of new energy is primarily project-based and concentrated in rural areas. (2) Financial support is a double-edged sword. (3) After the implementation of the Renewable Energy Law in 2015, the change trend in policy quantity, total policy intensity, and average policy intensity is generally consistent. (4) The increase in the strength of new energy policies has effectively reduced the intensity of provincial carbon dioxide emissions. (5) New energy policies introduced in a single region are less effective in reducing carbon emissions than joint regional regulation. Therefore, it is necessary to improve the quality and coordination of new energy policies through the effective convergence of policies and regular evaluations to enhance the positive guidance of the policies. Policy measures for new energy are refined in three areas: improving the amount and quality of new energy policies, strengthening new energy policies and establishing cooperation mechanisms for the cross-regional consumption of new energy.

The Carbon Emissions from Public Buildings in China: A Systematic Analysis of Evolution and Spillover Effects

Public buildings, being the primary source of carbon emissions in China’s construction sector, present a pressing need for emission control. This imperative task not only ensures the sustainable progression of China’s building industry but also holds pivotal significance in the realm of global energy conservation and emission curtailment. This study analyzed the spatiotemporal evolution of carbon emissions from public buildings in China and assessed the spatial influence of related factors using a dataset covering 30 provincial units from 2006 to 2021. The analysis employed Theil’s index, Moran’s I index, standard deviation ellipse, and the spatial Durbin model. The study revealed an upward trajectory in carbon emissions from public buildings in China, although the growth rate was generally decreasing. Disparities in emission distribution among provincial units stem largely from intra-regional distinctions, notably prominent in the Low-Intensity High-Economy regions. Provincial carbon emissions from public buildings exhibited significant spatial correlation, manifesting as clusters of high–high and low–low patterns, indicative of mutual influence among adjacent areas. Additionally, the shift in carbon emission focal points from the northeast to the southwest underscored a more pronounced surge in the southwestern regions. Variables such as energy intensity, energy structure, per capita public building area, disposable income per capita, openness level, and environmental governance directly impact carbon emissions from public buildings. Among these, energy intensity, energy structure, disposable income per capita, and environmental governance also had spatial spillover effects. These findings provide a scientific reference and a foundation for policy-making, aiding local administrations in crafting strategies to mitigate carbon emissions from public buildings and foster sustainable progress.

Harmonizing economies and ecologies: Towards an equitable provincial carbon quota allocation for China’s peak emissions

Rational provincial allocation of carbon quotas serves as the foundational premise for attaining China’s carbon peak. Yet, prevailing strategies often overlook the holistic integration of trade-induced carbon transfers and ecological carbon sequestration, resulting in equity and scientific robustness deficiencies. This study addresses these shortcomings by examining historical carbon sources and sinks across China’s provinces and proposing a novel provincial allocation scheme based on the ‘equal consumption-based cumulative per capita net emission’ principle. Our findings reveal significant disparities in the carbon quotas between provinces, ranging from ‒98 Mt in Shanghai to 1016 Mt in Sichuan, primarily influenced by factors such as population size, historical emissions, and carbon sinks. The proposed scheme, integrating considerations of carbon transfers and sinks, safeguards the interests of less developed provinces (e.g., Hebei and Inner Mongolia) and those with valuable ecosystems (e.g., Yunnan and Inner Mongolia). Furthermore, the impact of carbon transfers on provincial carbon allocation quotas is more pronounced than that of carbon sinks. For instance, the inclusion of carbon transfers has increased Inner Mongolia’s quotas by 238 Mt, compared to 125 Mt attributed to carbon sinks. Considering the disparities in emissions reduction pressure and capacity across different provinces, combining fair carbon quota allocation with a nationwide carbon market can achieve cost-effective emissions reduction while ensuring the attainment of carbon peak.

The Impact of Regional Carbon Emission Reduction on Corporate ESG Performance in China

The integrated planning of central and local emission reduction tasks is crucial for achieving sustainable economic development, and corporate ESG performance aligns with the principles of sustainable development, having become a prominent topic in academic research. This paper empirically investigates the impact of regional carbon emission reductions on the ESG performance of local enterprises from 2009 to 2021 using provincial carbon emission data from China. The findings indicate that regional carbon emission reductions significantly enhance the ESG performance of local firms. The underlying mechanism is that regional carbon emission reductions facilitate local enterprises obtaining green credit, attracting media coverage and green investors and thus improving ESG performance. Second, heterogeneity tests reveal that regional carbon emission reductions enhance the ESG performance of local firms more significantly in regions with stricter environmental regulations, within heavily polluted industries, and among less digitized enterprises. Finally, further analysis demonstrates that regional residents’ carbon emission reductions can enhance the ESG performance of local enterprises, with regional carbon emission reductions exerting a dual effect after improving ESG performance. The findings of this study provide valuable insights into the low-carbon development of various economic entities and the collaborative promotion of economic green transformation.

The Impact of the Digital Economy on Provincial Carbon Productivity: Empirical Evidence from China

With the introduction of the dual carbon goals of “carbon peak” and “carbon neutrality”, low-carbon economic development has become the focus of attention for all sectors in China. Improving carbon productivity (CP) is the key to developing a low-carbon economy and is essential to achieving carbon emission reduction and economic growth. The rapid development of the digital economy (DE) provides a new breakthrough for improving carbon productivity, but there are few studies on the digital economy and carbon productivity in the existing literatures. We empirically investigate the impact mechanism of the digital economy on provincial carbon productivity using China’s provincial panel data from 2010 to 2019. This study finds that the digital economy significantly raises provincial carbon productivity; this result remains valid after a series of robustness tests. The digital economy can impact provincial carbon productivity through both energy consumption structure (ECS) and green technology innovation (GTI) and can contribute to the improvement of provincial carbon productivity by optimizing energy consumption structure and improving green technology innovation. In addition, different environmental regulations have different impacts. Command-and-control environmental regulation (CER) weakens the positive impact of the digital economy on provincial carbon productivity, whereas market-based environmental regulation (MER) enhances the positive impact of the digital economy on provincial carbon productivity. This study extends the research on the digital economy in the field of low-carbon development, providing insights and policy suggestions for relevant departments to promote low-carbon development from the perspective of the digital economy.

Impact of capital market distortion on Chinese provincial carbon economy performance

Impact of capital market distortion on Chinese provincial carbon economy performance

Carbon Emission Heterogeneity in Developed Countries: Insights for China’s Neutrality Strategy

This study investigates the heterogeneity and driving factors of carbon emission reduction in developed countries, providing insights for formulating carbon neutrality strategies and plans in China. Firstly, typical developed countries worldwide are categorized into four modes: high energy consumption–high emissions, high energy consumption–low emissions, low energy consumption–low emissions and low energy consumption–high emissions, based on the “per capita energy consumption–emission intensity” classification method. Secondly, the LMDI decomposition model is employed to calculate the carbon emission-reduction driving effects of each mode, thereby analyzing the evolution path of carbon emissions. Finally, carbon emission-reduction policy recommendations are proposed based on the current situation of provincial carbon emissions in China. The research findings are as follows: (1) Carbon emissions in developed countries follow the Environmental Kuznets Curve (EKC) law, exhibiting an inverted U-shaped trajectory. In the per capita GDP range of USD 12,000–20,000, carbon emissions in most countries have reached or are close to their peak, with per capita carbon emissions in different modes decreasing and tending towards a level of 4000 kg/person. (2) There is heterogeneity in the EKC of carbon emissions in developed countries, which can be divided into technological, structural, comprehensive and clean types based on differences in emission-reduction factors. The trajectories of carbon emissions in most developed countries follow a clean path, while those in newly developed countries are constrained by environmental pressures and are expected to be between mixed and structural types before the emission peak, and tend towards a clean type after the peak. (3) Energy clean-up is the most direct and efficient method for carbon emission reduction, which can significantly and efficiently achieve carbon emission reduction. Industrial restructuring and technological progress play a significant role in suppressing carbon emissions. Policy recommendations are proposed as follows: first, reduce the proportion of fossil energy and increase energy cleanliness; second, promote industrial restructuring to reduce energy dependence; third, enhance production technology and improve energy-utilization efficiency; fourth, increase technological breakthroughs to support low-carbon transformation; fifth, correctly recognize the differences among provinces in China and formulate differentiated carbon emission-reduction policies.

Carbon Emissions Drivers and Reduction Strategies in Jiangsu Province

China embarked on the implementation of a comprehensive national strategy aimed at reducing greenhouse gas (GHG) emissions in 2020, with ambitious targets to achieve peak emissions by 2030 and attain carbon neutrality by 2060. Given the challenges, thoroughly investigating China’s carbon emissions status and outlining reduction pathways for each province is crucial. Based on calculating carbon emissions in Jiangsu Province, this article uses the Logarithmic Mean Divisia Index (LMDI) model to decompose and analyze the factors that affect carbon emissions. This article starts with provincial carbon emissions to find the core factors and then narrows the research scope to the city level to make carbon reduction policies more targeted. When decomposing carbon emissions, this article not only selects energy structure, energy efficiency, economic development, population size, and industrial structure factors commonly used in the LMDI model but also adds the factor of external electricity to research indirect carbon emissions. The final conclusions mainly include the following: firstly, the economic development and energy efficiency factors in Jiangsu Province are the core influencing factors for carbon emissions. The former promotes carbon emissions, while the latter reduces it, and the impact gradually weakens. The energy structure and industrial structure have reduced carbon emissions, while population size and electricity transfer have increased carbon emissions. Furthermore, notable disparities in carbon emissions exist among cities within Jiangsu Province, with varying impacts stemming from diverse driving factors. Upon comprehensive evaluation of the collective carbon reduction impact, Nanjing and Suzhou emerge as cities with a low contribution rate attributable to their industrial structure. Wuxi, Zhenjiang, and Xuzhou, on the other hand, exhibit a low contribution rate associated with their energy structure. Taizhou and Nantong demonstrate a low contribution rate in energy efficiency, while Changzhou, Huai’an, and Yangzhou display a low contribution rate in both industry and energy structure. Lianyungang, Suqian, and Yancheng present low contribution rates across all three factors. Recognizing the distinctive energy and industrial profiles of each city, governmental policies should be formulated with uniformity, fairness, and flexibility, effectively realizing the dual carbon objectives.