Analysis of carbon emission performance and regional differences in China's eight economic regions: Based on the super-efficiency SBM model and the Theil index.

China’s carbon emission performance has significant regional heterogeneity. Identified the sources of carbon emission performance differences and the influence of various driving factors in China’s eight economic regions accurately is the premise for realizing China’s carbon emission reduction goals. Based on the provincial panel data from 2005 to 2017, the super-efficiency SBM model and Malmquist model are constructed in this paper to measure regional carbon emission performance’s static and dynamic changes. After that, the Theil index is used to distinguish the impact of inter-regional and intra-regional differences on different regions’ carbon emissions performance. Finally, by introducing the Tobit model, the effect of various driving factors on carbon emission performance differences is analyzed quantitatively. The results show that: (1) There are significant differences in different regions’ carbon emission performance, but the overall carbon emission performance presents an upward fluctuation trend. Malmquist index decomposition results show substantial differences in technology progress index and technology efficiency index in different regions, leading to significant carbon emission performance differences. (2) Overall, inter-regional differences contribute the most to the overall carbon emission performance, up to more than 80%. Among them, the inter-regional and intra-regional differences in ERMRYR contributed significantly. (3) Through Tobit regression analysis, it is found that residents’ living standards, urbanization level, ecological development degree, and industrial structure positively affect carbon emission performance. On the contrary, energy intensity presents an apparent negative correlation on carbon emission performance. Therefore, to improve the carbon emission performance, we should put forward targeted suggestions according to the characteristics of different regional development stages, regional carbon emission differences, and influencing driving factors.

Can China's carbon intensity constraint policies improve carbon emission performance? Evidence from regional carbon emissions

Climate change resulting from CO2 emissions has become an important global environmental issue in recent years. Improving carbon emission performance is one way to reduce carbon emissions. Although carbon emission performance has been discussed at the national and industrial levels, city-level studies are lacking due to the limited availability of statistics on energy consumption. In this study, based on city-level remote sensing data on carbon emissions in China from 1992–2013, we used the slacks-based measure of super-efficiency to evaluate urban carbon emission performance. The traditional Markov probability transfer matrix and spatial Markov probability transfer matrix were constructed to explore the spatiotemporal evolution of urban carbon emission performance in China for the first time and predict long-term trends in carbon emission performance. The results show that urban carbon emission performance in China steadily increased during the study period with some fluctuations. However, the overall level of carbon emission performance remains low, indicating great potential for improvements in energy conservation and emission reduction. The spatial pattern of urban carbon emission performance in China can be described as “high in the south and low in the north,” and significant differences in carbon emission performance were found between cities. The spatial Markov probabilistic transfer matrix results indicate that the transfer of carbon emission performance in Chinese cities is stable, resulting in a “club convergence” phenomenon. Furthermore, neighborhood backgrounds play an important role in the transfer between carbon emission performance types. Based on the prediction of long-term trends in carbon emission performance, carbon emission performance is expected to improve gradually over time. Therefore, China should continue to strengthen research and development aimed at improving urban carbon emission performance and achieving the national energy conservation and emission reduction goals. Meanwhile, neighboring cities with different neighborhood backgrounds should pursue cooperative economic strategies that balance economic growth, energy conservation, and emission reductions to realize low-carbon construction and sustainable development.

Carbon emission accounting is the basic premise of effective carbon emission reduction and management. This study aimed to establish the carbon emission model and performance evaluation framework of coal mine production enterprises and clarify the low-carbon development path of enterprises. In this study, we took a typical coal production enterprise (K enterprise) in the Shanxi province of China as the research object. We also estimated the carbon emissions of the enterprise mainly according to the Chinese Carbon Emission Accounting Standard (GB/T 32151.11-2018). The triangular model was used to construct the carbon performance evaluation framework. On this basis, we suggested the enterprise's low-carbon development path. The results showed that (1) the carbon emission of K enterprise in 2021 was 36,875.38 tCO2eq; the carbon emission intensity of each ton of coal produced was 0.089 tCO2eq. The critical carbon emissions were electricity consumption and methane fugitive emissions during production. (2) The evaluation indicators for carbon emission performance revealed an imbalance in K enterprise's economic, energy, and environmental development in 2021. The work on energy saving and consumption reduction was relatively weak. (3) Countermeasures for low-carbon development, including a carbon emission ledger, were proposed based on carbon emission accounting and performance evaluation results. This study can help typical underground coal production enterprises in Shanxi province obtain more accurate carbon emission data, providing practical guidance and reference for the same underground coal production enterprises to improve the carbon emission control effect.

With the development of a low-carbon economy, corporate carbon emission performance has become an important premise for green financing. Compared with high-carbon industries, companies in low-carbon industries have their own carbon advantages and receive less attention. In order to highlight the value of carbon emission performance in low-carbon industries, further investigation on the basis of low-carbon industries is still needed. In terms of fixed assets, which are indicators for an important source of carbon emissions in intensive carbon industries, this study explores the relationship between asset structure, asset utilization efficiency, and carbon emission performance in low-carbon industries. This study selects Chinese listed companies from low-carbon industries that have disclosed their carbon emission performance from 2010 to 2021 as samples. The panel model is used for regression analysis, and then the Arellano-Bover/Blundell-Bond panel dynamic data model is used to solve the problem of endogeneity. The results show that the higher the fixed asset ratio, the worse the carbon emission performance. Asset utilization efficiency weakens the inhibitory effect of the fixed asset ratio on carbon emission performance. This study verifies the significant impact of fixed assets on the carbon emission performance of low-carbon industries as well as the promotion effect of asset utilization efficiency on carbon emission performance. Further investigation verified the promoting effect of corporate growth capabilities on carbon emission performance with two mechanisms, namely the relationship between fixed assets (independent variable)-asset utilization efficiency and (mediator)-corporate growth capabilities (dependent variable) or the relationship between asset utilization efficiency (independent variable)-corporate growth capabilities and (mediator)-fixed assets (dependent variable) from perspectives of enterprise value and expansion. This study expands the influencing factors of carbon emissions in low-carbon industries and is a theoretical supplement to a large number of high-carbon studies. At the same time, it also has certain implications for the carbon emission management practices of enterprises in low-carbon industries. It also reveals the urgency for the government and research institutions to clarify the carbon emission capacity of different fixed assets. Thus, it is convenient for low-carbon industries and high-carbon industries to carry out more refined carbon management and give full play to their carbon advantages.

Carbon emission performance (CEP) comprehensively considers the four-dimensional factors of “carbon reduction, pollution reduction, green expansion, and growth” and constitutes a key indicator for low-carbon and high-quality development. Although some studies have previously explored the relationship between regional integration and carbon emissions from different perspectives, it remains unclear how regional integration affects carbon emission performance. This article regards the regional integration construction of the Yangtze River Economic Belt as a quasi-natural experiment and uses the difference-in-difference (DID) model to empirically examine the mechanisms behind regional integration and their impact on carbon emission performance. The results show that regional integration significantly promotes improvements in carbon emission performance, primarily through three transmission mechanisms: resource factor allocation, economies of scale, and green innovation. It can also promote improvements in carbon emission performance in high-level carbon emission performance cities, middle- and downstream cities, non-natural-resource-oriented cities, and non-riverside cities. This article provides theoretical and empirical evidence that can be utilized to promote China’s high-quality, low-carbon transformation through regional integration construction in the Yangtze River Economic Belt.

PurposeThe objective of this study is to determine the impact of GHG assurance on firms’ carbon emissions performance (CEP) regarding curbing carbon emissions and the effect on such by the GHG assurance provider’s affiliation and reputation. It also explores whether the affiliation and reputation of GHG assurance providers imply the relationship between GHG assurance and the firm’s CEP. Further, this study examines the moderating effect of the country’s development level on the relationship.Design/methodology/approachBased on a sample of international firms from 56 countries spanning the period from 2012 to 2020, this study utilizes the ordinary least squares (OLS) regression. We also run the OLS regression at times t+1 and t+2 to verify the baseline results. To address the endogeneity concerns arising from self-selection bias and the causality effect, this study applies the generalized method of moment (GMM) and the Heckman test.FindingsThis study finds that GHG assurance leads to better CEP by firms. We also find that engaging with accounting assurance providers leads firms to a better CEP than non-accounting assurance providers. Our results show that Big Four auditors can help firms decrease carbon emissions. We also find that the positive effect of GHG assurance is prevalent in firms operating in developed countries.Research limitations/implicationsOur study only considers the influence of the assuror’s reputation and affiliation on CEP without examining other factors that may influence the quality of assurance services provided.Practical implicationsOur study provides a practical implication related to the influence of a GHG assurance provider’s affiliation and reputation globally by providing evidence that accounting and Big Four assurance providers do play a significant role in a firm’s carbon emission performance. This study offers great insights into the GHG assurance impact on CEP with the interplay between the assuror’s affiliation and reputation and the country’s development.Originality/valueThis paper enriches the limit evidence on GHG assurance and CEP by providing novel evidence on the relationship between GHG assurance and a firm’s CEP. Moreover, this study provides insights into the implication of a country’s development level on the role of GHG assurance in CEP.

This paper investigates the spatial and temporal evolution of the coordination between carbon emission performance (CEP) and ecological resilience (ER) in the Yellow River Basin, considering China’s active urbanization transformation and commitment to the “dual-carbon” target. We establish a comprehensive evaluation system using the super-efficiency SBM model and the entropy weight TOPSIS method. Additionally, we analyze the dynamic evolution and driving factors of CEP and ER in the region through Gaussian kernel density estimation and geographic detector. The findings reveal that: CEP in the Yellow River Basin fluctuates during 2011–2021, with a slight overall change, while ER shows a consistent increase. Notably, CEP decreases notably in the upstream, moderately in the middle reaches, and marginally in the downstream. Conversely, ER improves in the upstream but declines overall, with slight enhancements in the middle reaches and little change downstream. The coupling coordination degree of CEP and ER among prefecture-level cities in the Yellow River Basin exhibits fluctuating patterns, with modest increases in the middle and upper reaches and slight decreases in the lower reaches. Overall, the coordination degree is disordered, with regional disparities. High-value points were notable in the downstream in 2011, peaked in the midstream in 2017, but declined overall by 2021.The dynamic evolution of the coupling coordination degree of carbon emissions and ecological resilience reflects the complex interplay between urbanization, environmental policies, and geographic factors in the Yellow River Basin.

Carbon emission performance and quota allocation in the Bohai Rim Economic Circle

From a global perspective, carbon emissions are a global problem that needs to be solved urgently. At present, 61% of countries have committed to achieving net zero emissions. Compared with industry and construction, the transportation sector has become the focus and challenge for countries to achieve carbon neutrality due to the characteristics of strong mobility, scattered emission sources, and complex social behaviors. Therefore, the issue of carbon emissions in the transportation industry has become the focus of academic attention. This paper first calculates the carbon emission efficiency (CEE) of the regional transportation industry through the super-efficiency SBM model and then evaluates its regional differentiation characteristics through the Theil index, which has important practical significance for reducing regional carbon emissions. The results show that the national transportation CEE average value is 0.612, a relatively low level. The spatial distribution of China’s transportation CEE shows an obvious characteristic of “east highest and west lowest”. The regional differences in the transportation industry CEE are larger than those between regions. The differences in the transportation industry CEE among the eastern, central, and western regions are on the downward trend as a whole, and intra-regional differences are greater than inter-regional. The intra-regional differences cause the overall differences in transportation industry CEE; the eastern region contributed the most to the Theil index, while the central contributed the least. The biggest factor affecting the transportation industry CEE is the regional energy structure, and the smallest factor is the per capita GDP. This research has important reference significance on the target of carbon neutrality.

The two-sided effects of foreign direct investment on carbon emissions performance in China

"Carbon peaking" and "carbon neutrality" are serious challenges at this stage, and the function of the green transformation finance (GTF) in the operation of carbon dioxide emission reduction is an urgent issue to be explored. However, empirical studies on GTF and carbon emission performance (CEP) are lacking. Given that, this research employs a panel dataset of 278 cities in China spanning the years 2006 to 2020 to measure the CEP of Chinese cities using the non-radial directional distance function (NDDF) approach and applies the SPDM and the intermediary effect model to practically analyze the spatial effects and mechanisms of GTF in promoting CEP. The findings derived from the empirical analysis indicate that (1) the level of GTF and CEP shows a trend of year-on-year increase, and there is a significant spatial correlation, but the absolute difference in CEP between cities increases. (2) GTF promotes the improvement of CEP in local cities. It reveals a favorable spillover impact on enhancing the neighboring cities' CEP. Furthermore, the research findings remain pertinent even after conducting rigorous tests to ensure their robustness. (3) Regional heterogeneity has been observed in the impact of GTF on CEP, with the development of GTF significantly contributing to the amelioration of CEP of neighboring cities in the east, significantly contributing to the improvement of local CEP of central cities and simultaneously contributing to the improvement of local and neighboring cities' CEP in the west. (4) The findings of the intermediary examination show that GTF mainly promotes CEP through the positive incentive effect of promoting green innovation in technology and the reverse push-back effect of optimizing the structure of industries. (5) The spatial spillover effect of GTF on CEP is more sensitive under the geographic distance matrix, showing a "three-stage" decay characteristic from near to far, and its influence range is roughly 300km. Therefore, China should strengthen the development of GTF, cross-city communication and cooperation to boost the accomplishment of the carbon neutrality objective.

To support China’s “3060” dual carbon targets, this study quantitatively evaluates the spatial–temporal characteristics and influencing factors of carbon emission performance (CEP) across administrative levels. While prior research has examined CEP patterns, a systematic comparison of factor contributions at different levels—particularly from global and local perspectives—is lacking. This study addresses this gap by analyzing CEP in 31 provinces and 333 prefecture-level cities (2003–2020) using a coupling coordination degree model to measure CEP, spatial autocorrelation indices (Moran’s I) to assess global/local dependence, static/dynamic Spatial Durbin model (SDM/DSDM) with two-way fixed effects to compare global impacts, and geographically and temporally weighted regression (GTWR) to quantify spatiotemporal heterogeneity. The results show the following: (1) CEP showed consistent growth at both levels with positive spatial autocorrelation, revealing significantly richer clustering patterns at the prefectural rather than provincial level. (2) From a global perspective, influencing factors’ contributions to CEP vary significantly between levels. Provincially, dominant factors rank as time-lagged CEP(CEP_lag)> proportion of built-up land(P_built) > spatial lag of CEP(W×CEP) > fractional vegetation coverage (lnFVC); while prefecturally, CEP_lag > spatial error coefficient(rho) > W×CEP > P_built, with the proportion of secondary industry in GDP (GDP2)/proportion of tertiary industry in GDP (GDP3) gaining greater significance. (3) Local regression results reveal significant spatiotemporal heterogeneity in CEP influencing factors. lnFVC and W×CEP show the most distinct differences between levels, while land-use factors like P_built and nighttime light index (NTL) exhibit unstable spatiotemporal effects. The study underscores the need for scale-specific policies addressing spatial spillovers and local heterogeneity, providing actionable insights for China’s carbon mitigation strategies.

New quality productivity (NQP) has the possibility to enhance carbon emission performance which will fortify the groundwork for long-term economic expansion even further. The research examines the panel data of 30 provinces spanning the years 2012 to 2022 for an evaluation framework for NQP and carbon emission performance at the provincial level. Employing fixed effect models, mediation effect analysis, and spatial econometrics, the study explores the effect of NQP on carbon emission performance, its mediating mechanisms, and the spatial spillover effects. The findings indicate that (1) NQP significantly lowers carbon emissions for every unit of GDP and enhances carbon emission performance, and the result holds up when the instrumental variable methods are used. (2) The NQP had a significant contribution to improving carbon emission performance via advancements in green innovation. (3) The NQP does more than directly enhance the regional carbon emission performance; in contrast, it additionally positively influences the carbon emission performance level of the adjacent regions by the spatial spillover effect. (4) The impact of NQP on carbon emission performance is particularly pronounced in eastern and innovative regions. On this basis, we should vigorously develop the NQP, strengthen cross-regional policy coordination, and promote green and sustainable development.

Resource-based cities had an irreplaceable role in the process of the economic miracle in China. Advancing such cities’ carbon emissions reduction is a crucial aspect of the country’s steady realisation of the dual carbon peak and neutrality strategy. The reasonable implementation of environmental regulation and the efficiency of factor marketisation allocation are the key links for resource-based cities to improve carbon emissions performance, break the resource curse and reduce carbon emissions. Based on this, this study centres on the driving relationship between environmental regulation, the efficiency of factor marketisation allocation and carbon emissions performance as the core research problem. This study takes the panel data of 116 resource-based cities in China from 2006 to 2020 as the research sample; the non-radial meta-frontier total factor carbon emissions performance index is selected as the measurement index of carbon emission performance of resource-based cities based on the applicability analysis of the model. This study explores the characteristics of regional heterogeneity and type heterogeneity of carbon emissions performance driven by environmental regulation under the moderating effect of the efficiency of factor marketisation allocation and further explores the threshold effect, aiming to clarify the driving relationship between the three. The findings reveal that the driving effect of environmental regulation intensity on carbon emissions performance exhibits a fluctuating upward trend, the effect transformed by compliance cost and innovation compensation. The efficiency of factor marketisation allocation has a double threshold superposition effect on carbon emissions performance fluctuation that is driven by environmental regulation, indicating that market and government effectiveness can operate together to improve the carbon emissions performance. Based on these results, this study proposes countermeasures and suggestions for improving carbon emissions performance using environmental regulation and the efficiency of factor marketisation allocation.