Inter-provincial Carbon Emission Research Articles

What influences the performance of carbon emissions in China?-Research on the inter-provincial carbon emissions' conditional configuration impacts.

The severe global warming issue currently threatens humans' existence and development. Countries and international organizations have effectively implemented policies to reduce carbon emissions and investigate low-carbon growth strategies. Reducing carbon emissions is a hot topic that academics and government policy-making departments are concerned about.Through necessary condition analysis (NCA) and fuzzy set qualitative comparative analysis(fsQCA), this paper investigates local governments' configuration linkage effect and path choice to improve carbon emission performance from six dimensions: energy consumption, industrial structure, technological innovation, government support, economic development, and demographic factors. The research findings include the following: (1) Individual condition does not represent necessary conditions for the government's carbon performance. Among the two sets of second-order equivalence configurations(S and Q) (five high-level carbon performance configurations), those dominated by economic development or low energy consumption can produce high-level carbon performance. Therefore, the six antecedent conditions dimensions work together to explain how the government can create high levels of carbon performance. (2)According to the regional comparison, China's eastern, central, and western regions exhibit similarities and differences in the driving forces behind high carbon emission performance. All three regions can demonstrate carbon emission performance when all the factors are combined. However, when constrained by the conditions of each region's resource endowment, the eastern region emphasizes the advantage of economic and technological innovation, the central region favors government support and demographic factors, and the western region prefers upgrading industrial structure based on a specific level of economic development.

Spatiotemporal heterogeneities in the impact of the digital economy on carbon emission transfers in China

This study investigates the spatiotemporal impacts of digital economic development on interprovincial carbon emissions transfer in China. Applying a proposed mixed geographically and temporally weighted spatial interaction panel regression (MGTWIPR) model, the study analyzes the annual carbon emissions data of 31 provincial administrative regions in China from 2015 to 2017. The results show that China's interprovincial carbon emissions transfers have apparent asymmetrical and imbalanced characteristics. The most significant transfers from the Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions to north China and its surrounding areas follow a general pattern of carbon emissions transfer from developed to less developed regions. Improving digital economic development in origin regions promotes the exportation of carbon emissions to other areas. Conversely, enhancing digital economic development in destination regions would inhibit the import of carbon emissions to those regions. Additionally, from a spatial perspective, the impact of the origin region's digital economic development on carbon transfer is maximized in western China. Temporally, the influence of the origin region's digital economic development on carbon emissions transfers increases over time. This study integrates research regarding the digital economy and carbon emissions transfer, providing a novel perspective for digital economic studies. It also introduces a new research method for investigating the spatiotemporal heterogeneity of panel data. The results suggest the development of targeted strategies for regions with net carbon emissions exports and imports, emphasizing the role of digital technology in curbing carbon emissions to meet China's dual carbon goals.

A bi-level multi-objective optimization model for inter-provincial carbon emissions transfer tax on electricity production

Low-carbon electricity development is crucial for achieving China's carbon peaking and carbon neutrality goals. The current carbon reduction territorial management model (CRTMM) can only bring short-term carbon reduction and is not enough to motivate provinces to further reduce carbon. However, few studies focus on the inter-provincial coordinated electricity carbon reduction. To overcome the shortcomings of the CRTMM and fill the research gap, this study creatively presents an original bi-level multi-objective inter-provincial carbon emissions transfer tax model (CETTM) on electricity generation in China, where the central government is the upper-level decision maker (leader) and provincial governments are the lower-level decision makers (followers). As the leader, the central government pursues overall maximum economic benefit and minimum pollutant emissions, and as the followers, provincial governments endeavor to maximize internal economic benefits. To ensure the scientificity and accuracy of the calculation results, an improved NSGA-II algorithm is designed to solve the model. Data from Anhui, Qinghai, Heilongjiang, and Jiangsu provinces are then used for empirical analysis to validate the model. The findings demonstrate that the CETTM is superior to the CRTMM in reducing carbon emissions, lowering pollutant emissions and improving economic benefits. The CETTM reduces CO2 emissions by 20.04 × 106 tons, lowers pollutant emissions by 10.65 × 104 tons, and increases benefits by 101.99 × 108 CNY in contrast to the CRTMM. The robustness of the model is verified using a sensitivity analysis. Finally, this study proposes policy recommendations for the CETTM implementation.

The Classification Impact of Different Types of Environmental Regulation on Chinese Provincial Carbon Emission Efficiency

The evaluation of inter-provincial carbon emission efficiency and the analysis of its influencing factors hold great practical significance for reducing carbon emissions and promoting sustainable development in ecological management. To address the shortcomings of existing research in the classification evaluation of carbon emission efficiency and account for the impacts of different environmental regulatory policies on carbon emissions, this paper aims to examine the impact of formal and informal environmental regulations on carbon emission efficiency. This is accomplished by utilizing a combination of the data envelopment analysis (DEA) model, entropy weighting, and k-means cluster analysis methods. The fixed-effects model is also applied to examine the influences of different factors on carbon emission efficiency under different categories. To conduct the case studies, carbon emission management data from 30 provinces in China are collected, and the results show the following: (1) Formal environmental regulations exhibit a “U-shaped” relationship with carbon emission efficiency, whereas informal environmental regulations have an “inverted U-shaped” relationship with carbon emission efficiency. (2) Under the cluster analysis of carbon emission efficiency, formal environmental regulations are found to have a stronger incentive effect on inter-provincial carbon efficiency compared to informal environmental regulations. This study carries significant theoretical and practical implications for China’s timely attainment of its double-carbon target.

Research on Embodied Carbon Transfer Measurement and Carbon Compensation among Regions in China.

The existence of interprovincial embodied carbon transfer not only makes it difficult to achieve carbon emission reductions but also exacerbates the inequity, inefficiency, and high costs of interprovincial carbon emission reduction rights and responsibilities. This paper uses multi-regional input-output analysis (MRIOA) to measure the interprovincial embodied carbon transfer in 2017, obtains the net carbon transfer between 30 provinces (municipalities and autonomous regions) and eight regions in 2017, and accounts for the interprovincial carbon compensation amount based on the carbon price in the national carbon market. This study finds that carbon transfer from economically developed provinces to less developed provinces still exists in China, and the overall distribution shows a spatial transfer pattern from south to north and from east to west, with the northwestern region bearing most of the carbon emission pressure for which it should receive corresponding financial compensation. As part of the process to achieve the "dual carbon" target, appropriate emission reduction policies should be formulated according to the characteristics of provincial carbon transfer and the principle of "who benefits, who compensates", and economically developed regions should give corresponding financial or technical compensation to less developed regions based on net carbon transfer. Compensation and support should be given to less developed regions based on net carbon transfer to prevent further regional development imbalances.

Impact of Major Events on Interprovincial Carbon Emissions—Based on PSM-DID Analysis

The success of major events can enhance national image, boost people’s confidence, and alleviate the current “three-fold pressure”—contraction in demand, supply shocks and weak expectations. In the context of the carbon neutrality target, it is important to analyze the relationship between major events and carbon emissions as the ecological, social and economic systems become more closely related. To study the extent and persistence of the impact of major events on the carbon emissions of the hosting provinces, this paper collects annual carbon emission data from 2015 to 2019 for 30 provinces in China. The propensity score matching Difference in Difference model (PSM-DID) is used to explore the impact of major events, such as political conferences, sports events and cultural exchanges, at the national level on inter-provincial carbon emissions. The empirical study shows that (1) the carbon emissions of the provinces involved in major events significantly increase in the year when the major event is held, (2) the carbon emissions of the province significantly decrease in the year after the conclusion of the major event, and (3) the decrease is higher than the increase in carbon emissions in the year when the event is held. Finally, the model results are analyzed in the context of economic events and macroeconomic policy lags during the preparation period of the event, and policy suggestions are made to incorporate carbon neutrality into the overall layout study of ecological civilization construction, strengthening the construction of legal thinking, enhancing inter-provincial and inter-city pollution synergy control, innovating carbon-related technologies, unifying carbon emission accounting and improving data openness.

A Study of Carbon Emission Efficiency in Chinese Provinces Based on a Three-Stage SBM-Undesirable Model and an LSTM Model.

As a major carbon-emitting country, there is an urgent need for China to reduce carbon emissions. Studying the carbon emission efficiency of each province helps us to learn about the characteristics and evolution of regional carbon emissions, which is important for proposing effective and targeted measures to achieve the carbon peaking and carbon neutrality goals. This paper measures the carbon emission efficiency of 30 Chinese provinces from 2006 to 2019 based on a three-stage SBM-undesirable model and explores external drivers using stochastic frontier models. The results of the SBM-undesirable model show that the inter-provincial carbon emission efficiency is unevenly distributed and shows a big difference. From the results of the stochastic frontier model analysis, external drivers such as the intensity of finance in environmental protection, the level of economic development, the industrial structure, the level of urbanization, the degree of openness and the level of science as well as technology innovation all have an impact on the emission efficiency. In terms of LSTM model prediction, the model shows an excellent fitting effect, which provides a possible path for carbon emission efficiency prediction. Finally, based on the empirical results and the actual situation of each province in China, this paper proposes relevant feasible suggestions.

Carbon Transfer Decision Model Based on LMDI Method.

Establishing a coordinated governance mechanism for regional carbon emissions is an essential way to achieve carbon peak and carbon neutrality, while the study of interprovincial carbon emissions transfer is one of the important foundations of regional carbon emissions coordinated governance research. Based on the multiregional input-output (MRIO) model, this study calculated the carbon emissions from both the producers' perspective and the consumers' perspective and analyzed the interprovincial net carbon emissions transfer decision. Furthermore, the logarithmic mean Divisia index (LMDI) method was adopted to decompose the factors that affect the province's net carbon emissions into technological effect, structural effect, input-output effect, and scale effect. It was revealed that the input-output effect was the primary influencing factor of the net carbon transfer at the provincial level.

Is the "pollution haven hypothesis" valid for China's carbon trading system? A re-examination based on inter-provincial carbon emission transfer.

In recent years, China had released various environmental regulations in order to respond climate change and corresponding environmental issues. However, due to imbalanced economic development and industrial structure, different Chinese regions had different enforcement levels on environmental regulations, which led to the regional transfer of pollution-intensive industries. To study the regional disparities on carbon emission transfer, this paper used the propensity score matching-difference in differences method (hereinafter abbreviated as "PSM-DID") to evaluate the mechanism between carbon trading pilot policies and the transfer of pollution-intensive industries. Panel data on 30 Chinese provinces were used to test the validity of the "pollution haven hypothesis," covering the period of 2010-2018. The empirical results showed that under the constraints of established environmental regulation, the pilot policy promoted the transfer of pollution-intensive industries to a certain extent and verified the "pollution haven hypothesis"; the proportion of the secondary sector and energy industry in the pilot areas had been reduced after the pilot policy; on the contrary, the technical level and the economic development level of the pilot provinces and cities had been further improved.

Spatial effects of carbon emission intensity and regional development in China.

Due to the imbalance of technological level and industrial structure in regional economic development, the same carbon source can bring differentiated carbon emission levels in different regions, thus making the carbon emission show significant regional differences. In order to explore the regional differences in China's provincial carbon emission intensity and the effect of relevant influencing factors, this paper combines EKC model and STIRPAT model to conduct research. Using carbon emission intensity and other influencing factors of China's 30 provinces ranging from 2005 to 2017 to construct a panel data, the authors use exploratory spatial data analysis and Spatial Durbin Model to study the spatial effect of carbon emission intensity in China's provincial regions and the impact of different development factors on carbon emission intensity. The results show that from 2005 to 2017, China's carbon emission intensity gradually declined from east to west and from south to north. The inter-provincial carbon emission intensity of China presents an agglomeration effect in space, and the agglomeration effect gradually weakens with time. In addition, reducing energy intensity can reduce carbon emission intensity to a large extent. By optimizing industrial structure, increasing the degree of foreign trade and promoting financial development, carbon emission intensity can also be inhibited. Therefore, reducing the energy intensity of various industries and establishing inter-regional carbon emission cooperation mechanism will be effective to control the carbon emission intensity.

China’s initial allocation of interprovincial carbon emission rights considering historical carbon transfers: Program design and efficiency evaluation

Establishing a fair and reasonable initial allocation scheme for carbon emission rights is a prerequisite for the efficient and stable operation of the carbon market and an important guarantee for China to achieve its emission reduction target. This study considers the historical transfer of carbon emissions and measures the cumulative net carbon emissions of China's provinces based on the principle of consumer responsibility. It draws up an initial allocation plan for carbon emission rights in China's provinces in 2020, based on the principles of equity, efficiency, and sustainability. The carbon emission and carbon intensity efficiencies of the provinces under this distribution scheme were also evaluated. The results show that the historical net carbon export area mainly consists of energy-intensive provinces and economically underdeveloped poor and remote provinces. Additionally, the historical net carbon import area mainly consists of energy-starved and economically developed provinces. Provinces with high-value ecological services (Xinjiang, Heilongjiang, and Inner Mongolia) or with large economies and dense populations (Shandong, Guangdong, and Sichuan) will receive higher carbon emission rights, while those with developed economies (Shanghai, Beijing, and Tianjin) will receive lower carbon emission rights. Provinces with a good ecological environment (Inner Mongolia, Heilongjiang, and Xinjiang) as well as certain economically underdeveloped western provinces (Chongqing, Sichuan, and Yunnan) will have abundant carbon space in the future. Provinces with rapid economic development (Beijing, Shanghai, and Jiangsu) and resource-based provinces (Shanxi and Liaoning) with a high historical carbon output have little carbon space. Considering the historical carbon transfer, the carbon emission rights allocation system will benefit resource-based industrial provinces (Shanxi, Inner Mongolia, and Liaoning) and less developed western provinces (Shaanxi, Ningxia, and Xinjiang) in improving their carbon emission efficiency. This study provides a new research idea for formulating a more equitable and efficient allocation scheme for carbon emission rights.

An analysis on the adoption of an interregional carbon emission reduction allocation approach in the context of China’s interprovincial carbon emission transfer

Due to interregional carbon emission (CE) transfer, the CE reduction allocation approach is crucial to the overall CE reduction effect. The prevalent allocation mode applies the production-based principle (PBP) and causes equity and efficiency losses of CE reduction. The exploration of a CE reduction policy under the consumption-based principle (CBP) is highly demanded. In this article, by studying the transfer of CEs embodied in interprovincial trade (CEs-PT) in 1997–2007 within China, we propose a CE reduction allocation approach under the CBP. We found that net CEs-PT were huge and had increased from 172.22 million tons (Mts.) to 425.94 Mts. The main transfer flow was from the resource-based provinces to the economically developed provinces, from North China to South China. Under the PBP, the transfer of CEs-PT caused serious equity and efficiency losses of CE reduction in China. Then, we propose a CE reduction allocation approach under the CBP that considers the long-term dynamic change of regional CEs. The approach can eliminate equity loss, improve CE reduction efficiency, and avoid the impact of short-term fluctuations of regional CEs. Based on this approach, we calculated China’s provincial CE reduction responsibility and found that compared with the allocation approach under the PBP, the CE reduction responsibility of most net exporters of CEs-PT decreased, while that of most net importers increased. To accomplish CE reduction efficiently and economically, we propose a CE reduction trading system. The research can provide support for CE reduction allocation policy and CE reduction trading system for China and other countries.

Revealing environmental inequalities embedded within regional trades

Carbon emissions embodied in interprovincial trade (CEE-IT) are closely related with the environmental responsibility allocation. Besides the perspective of administrative division, more rational and effective clusters based on provincial characteristics is more conducive for understanding the regional emission reduction linkages and simplifying the steps of responsibility determination. To provide a reasonable management of CEs transference mitigation in China, this study develops a provincial clustering scale CEE-IT model through three-scale accountings (i.e., aggregated-scale, consumption-scale and income-scale analysis). Specifically, 30 provinces are aggregated into several new regions with similar characteristics. Carbon emissions from different energy sources are first considered to distinguish and specify different emission reduction modes. The input output analysis (IOA) and structural decomposition analysis (SDA) are applied to quantify the embodied interprovincial carbon emissions and the relative contributions of socio-economic factors at the sector-level of disaggregation and aggregation, respectively. Three-scale accountings are innovatively employed into EEBT model to deeply analyze the emissions along China’s domestic inter-regional supply chains for identifying regional production, consumption and income-based emission responsibilities. Based on three accounting perspectives, the results provide suggestions for coordinated emission reduction across regions (including specific provinces) from the overall and decomposition levels. It shows that cutting the imports of mining sector for all regions could reduce emissions from the supply side. Rural household consumption and fixed capital formation are the major drivers for Ⅳ region from the consumption side. Technological innovations in Ⅲ region have reduced carbon emissions by 55.2% and contributed 159 Mt reductions from 2007 to 2012. Ⅲ region is insensitive to energy types and the utilization of crude oil in Ⅰ region limit the improvement of its system efficiency. Importing large quantities of emission-intensive products from Beijing and Jiangsu is a cause of high income-based emissions in Ⅱ region.

The environmental effect of capacity utilization in thermal power plants: evidence from interprovincial carbon emissions in China.

As the largest emitter of CO2 emissions, the installed capacity of thermal power generation in China is facing more and more strict restrictions, since the Chinese government proposed to dissolve overcapacity and intends to solve the problem of continuous reduction in utilization rate of electricity sector. Regretfully, the impact of power-generating capacity and its utilization on carbon emissions in the power sector has not yet been addressed. In this study, we incorporate the interaction between capacity and utilization of power sector into the dynamic spatial Durbin model, and estimate the specific impact on carbon dioxide emissions from the power sector based on the panel data set of China's provinces during 1991-2015. The results show that both installed capacity and utilization rate have positive effects on CO2 emissions. Interestingly, the estimation coefficient of their interaction term is negative, implying that the carbon emission reduction effect derives from the conflicting performance of capacity governance and utilization efficiency. Besides, the advantage of the emerging econometric method, the dynamic spatial Durbin model (SDM) with provinces and time-period fixed effects, is that it can estimate spatial interaction effects among the provinces and neighboring provinces and decompose those effects into two parts: long-term and short-term. However, the estimates indicate that only capacity has roughly significant spatial spillovers. As a result, dissolving overcapacity of thermal power generation and a necessary interprovincial coordination will promote carbon emission reduction rather than investing in coal-fired power plants, and the power authority should turn to alternative investment in cleaner power generation technologies.

Regional-Level Allocation of CO2 Emission Permits in China: Evidence from the Boltzmann Distribution Method

To achieve the commitment of carbon emission reduction in 2030 at the climate conference in Paris, it is an important task for China to decompose the carbon emission target among regions. In this paper, entropy maximization is brought to inter-provincial carbon emissions allocation via the Boltzmann distribution method, which provides guidelines for allocating carbon emissions permits among provinces. The research is mainly divided into three parts: (1) We develop the CO2 influence factor, including per capita GDP, per capita carbon emissions, carbon emission intensity and carbon emissions of per unit industrial added value; the proportion of the second industry; and the urbanization rate, to optimize the Boltzmann distribution model. (2) The probability of carbon emission reduction allocation in each province was calculated by the Boltzmann distribution model, and then the absolute emission reduction target was allocated among different provinces. (3) Comparing the distribution results with the actual carbon emission data in 2015, we then put forward the targeted development strategies for different provinces. Finally, suggestions were provided for CO2 emission permits allocation to optimize the national carbon emissions trading market in China.

Provincial transfers of enabled carbon emissions in China: A supply-side perspective

The development of the regional economy in China is unbalanced. Interregional "carbon leakage" and "carbon transfer" have a significant impact on the realization of carbon emission mitigation targets and the allocation of responsibility. Using China's interregional input-output tables and the corresponding carbon emission data for 2007 and 2010, this paper proposes an interregional Ghosh input-output model and estimates the amount of interprovincial carbon emission transfer from the supply-side perspective. We find that the main direction of supply-side carbon emission transfer is from resource-intensive provinces in the central and western regions to developed provinces in the eastern coastal regions. Further analysis shows that the transfer is mainly concentrated in the production and distribution of electricity and heat, nonmetallic mineral products, and basic metals, whose carbon emissions account for approximately 70% of all sectors’ carbon emissions. The differences between the supply side and the demand side of China's provinces are mainly reflected in the transfer out of carbon emissions.

Contrastive analyses of the influence factors of interprovincial carbon emission induced by industry energy in China

As a major contributor of carbon emission in the world, China should focus on the balance between the universality of development and regional heterogeneity of carbon discharge during the transformation toward low-carbon economy. To reveal the differences among interprovincial industry energy’s carbon emissions, some relevant data of carbon emissions in 29 provinces and municipalities during the period of 1996–2012 are selected in this study. Based on the Logarithmic Mean Divisia index decomposition model and hierarchical clustering method, the 29 provinces were clustered in turn by four time intervals according to some indicators, including economic intensity, energy intensity, industry structure, energy structure, demographic effect, and carbon density influence. Research results show that during 1996–2000, economic intensity has a strong positive driving effect on carbon emissions in such eastern provinces as Shanghai, Zhejiang, and Jiangsu, and other seven inland provinces, such as Hunan and Hubei. Demographic effects have strong pulling effects on carbon emissions in municipalities and eastern coastal provinces, and they also exert strong negative effects on carbon emissions in Anhui, Guangxi, Guizhou, and Sichuan in the first three time intervals. During the four periods, highly energy-efficient provinces are Jiangsu, Guangdong, Sichuan, Shandong, Hubei, etc., whose carbon emissions are significantly inhibited by their energy intensity, whereas inefficient provinces are concentrated in western regions, like Guangxi, Hainan, Gansu, Qinghai, Ningxia, Xinjiang, etc.

An inquiry into inter-provincial carbon emission difference in China: Aiming to differentiated KPIs for provincial low carbon development

Reasonable formulation of carbon emission reduction strategies at sub-national scale is an important technique to realize the national target. However, a set of binding unified key performance indicators (KPIs) is usually not conducive to equitable regional development. Our study employs a hybrid carbon emission estimation method and a multi-index joint representation approach to explore the inter-provincial energy-related carbon emission difference in the year of 2012 in China. Stepwise regression method and hierarchical clustering model were used to classify 30 provinces into economically developed low-carbon region, industrially optimized low-carbon region, resource-abundant high-carbon region, and economically developing high-carbon region. Different regions should take differentiated measures and KPIs related to the local government's efforts to promote low carbon roadmap according to local conditions: The lack of natural resource provides the impetus to improve energy structure in the economically developed low-carbon region. The industrially optimized low-carbon region should place great importance on economic growth and per capita GDP improvement. The low-carbon transformation strategy of the resource-abundant high-carbon regions should focus on carbon emission reduction performance and carbon intensity decline. For economically developing high-carbon regions, decision makers should conduct a sound SWOT analysis of regional low carbon development.