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At present, to comply with carbon reduction commitments, China has only required energy-intensive enterprises to report their carbon information to regulators, aside from mandatory public disclosures. Although some enterprises have been disclosing their own carbon information voluntarily by means of corporate reports in order to shape their green image, their carbon information disclosures (CID) still need to be improved. This study attempts to systematically investigate links between corporate growth, carbon emission (CEP) or reduction performance (CRP) in two forms (intensity and amount), and CID in industries with different carbon intensities on the basis of stakeholder theory as well as legitimacy theory. This study took Chinese companies listed on the main board market from 2009 to 2021 as samples. The Arellano–Bover/Blundell–Bond dynamic panel data model was used for regression analysis. Results showed that sustainable growth enhanced the promotion effect of CEP (both in terms of intensity and amount) on CID in carbon-intensive industries, while sustainable growth enhanced the inhibition effect of CEP measured in terms of amount, rather than intensity, on CID in low-carbon industries. This revealed that CEP, not CRP, had a significant influence on CID, and uncovered the influence mechanism between carbon performance and CID from the perspective of sustainable enterprise growth. The carbon information disclosure of high-carbon industries is closely and positively related to carbon performance, indicating that the interaction between high-carbon industries and capital markets will be more affected by the mitigation of carbon information asymmetry. Further, circulating A-shares are moderators for better CID in both carbon-intensive industries and low-carbon industries, which fits the expectation of stakeholder theory as well as legitimacy theory. Additionally, measurement habits or preference for carbon emissions performance (in the form of amount or intensity) in different industries should be brought to the forefront to enhance investors’ confidence in CID. This study has certain guiding value for the formulation of CID standards and contributes to the process of mandatory CID.

Industry is a major contributor to carbon emissions in China, and industrial land is an important input to industrial production. Therefore, a detailed analysis of the carbon emission performance of industrial land use is necessary for making reasonable carbon reduction policies that promote the sustainable use of industrial land. This paper aims to analyze the dynamic changes in the total-factor carbon emission performance of industrial land use (TCPIL) in China by applying a global directional distance function (DDF) and non-radial Luenberger productivity index. The empirical results show that the eastern region enjoys better TCPIL than the central and western regions, but the regional gaps in TCPIL are narrowing. The growth in NLCPILs (non-radial Luenberger carbon emission performance of industrial land use) in the eastern and central regions is mainly driven by technological progress, whereas efficiency improvements contribute more to the growth of NLCPIL in the western region. The provinces in the eastern region have the most innovative and environmentally-friendly production technologies. The results of the analysis of the influencing factors show implications for improving the NLCPIL, including more investment in industrial research and development (R&D), the implementation of carbon emission reduction policies, reduction in the use of fossil energy, especially coal, in the process of industrial production, actively learning about foreign advanced technology, properly solving the problem of surplus labor in industry and the expansion of industrial development.

To achieve carbon peak targets, realize carbon neutrality vision, and tackle global climate change, China must improve the carbon emission performance at the city level. Based on the carbon emission performance of 191 prefecture-level cities in China from 1997 to 2017, this paper analyses the evolution characteristics of urban carbon emission performance from three aspects: the overall spatial and temporal evolution, the differences according to both region and city size, and the differences among clusters categorized by carbon emission performance at the city level. This paper also reveals the impact of the social and economic transition on China’s carbon emission performance. The results show that: (1) The overall level of carbon emission performance of Chinese cities is low, and there is a downward trend during the study period. The differences in carbon emission performance among cities are convergent, but there is a wide gap between high and low values. (2) The carbon emission performance of cities in eastern coastal areas is higher than that in non-coastal areas cities. Large urban agglomerations and economically developed regions, such as provincial capitals, are the agglomeration areas of high urban carbon emission performance values. (3) The carbon emission performance level of cities with similar sizes will converge. At the same time, such changes will enhance the differences among carbon emission performances at the city level within the same region. (4) Cities that belong to high urban carbon emission performance clusters are mainly distributed in the eastern region. Such cities are classified into large cities, supercities, and megacities. Compared with low urban carbon emission performance clusters, cities in high urban carbon emission performance clusters show a higher proportion in the medium-high level and high level of carbon emission performance. Moreover, cities in high urban carbon emission performance clusters are more likely to improve theirurban carbon emission performance. (5) The economic agglomeration effect, industrial structure adjustment and carbon intensity reduction have a significant impact on improving urban carbon emission performance. Population agglomeration has an incremental effect, and the anticipated benefits of environmental regulation have yet to be fully realized. The impacts of different clusters and different regions are variable. Finally, this paper advances policy enlightenment according to its research findings.

The environmental issue has attracted ever-increasing attention from governments and academics in recent years. Environmental performance analysis is widely considered a crucial and useful tool for effectively protecting the environment and developing a sustainable society. Many analytical techniques have been used to assess carbon emission performance, among which data envelopment analysis (DEA) is prominent. However, few previous DEA-related carbon emission performance studies recognize that the total amount of carbon dioxide emissions is limited to a specific level by authorities; ignoring this fixed-sum requirement may lead to distortions and deviations in empirical results. This paper proposes an alternative Malmquist DEA approach for evaluating the carbon emission performance while considering fixed-sum undesirable outputs. For this purpose, we develop a generalized equilibrium efficient frontier DEA model with fixed-sum undesirable outputs and combine the model with the Malmquist productivity index (MPI). The proposed approach is applied to assess the carbon emission performance of 30 provincial regions in China from 2009 to 2015. Then we provide analytical results and policy suggestions regarding the provincial carbon emission performance in China.

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 tCO 2eq ; the carbon emission intensity of each ton of coal produced was 0.089 tCO 2eq . 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.

Climate change resulting from CO 2 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.

As a pivotal driver that facilitates the concentration of green innovation elements in key areas of energy conservation and emission reduction, new quality productive forces (NQPF) play a crucial role in carbon emission governance. Based on panel data from 108 prefecture-level cities in the Yangtze River Economic Belt (YREB) spanning 2010 to 2022, this study employs a mediation effect model and a spatial Durbin model (SDM) to empirically examine the mechanisms through which NQPF influence carbon emission performance (CEP), measured by carbon emission intensity (CEI) and carbon emission efficiency (CEE), as well as their spatial spillover effects. The results reveal that NQPF significantly reduces CEI and enhances CEE, and these findings remain robust across multiple tests. Mechanism analysis indicates that NQPF affects urban CEP through two main pathways: green technological innovation and industrial structure rationalization. Furthermore, environmental regulation intensity plays a significant positive moderating role in both pathways. Heterogeneity analysis shows that the inhibitory effect of NQPF on CEI is more pronounced in cities with lower levels of economic development, lower emission intensity, and in designated low-carbon pilot cities. In contrast, the positive effect of NQPF on improving CEE is more significant in cities with higher levels of economic development, higher emission intensity, and low-carbon pilot cities. Spatial effect analysis indicates that NQPF not only improves local CEP but also generates positive spillover effects on neighboring cities. This study provides both theoretical insights and practical implications for enhancing green technology innovation, promoting industrial structure optimization, and improving environmental regulation policies.

Improving urban comprehensive carbon emission performance (CCEP) is the inevitable choice for China’s low-carbon development. With the continuous integration of digital technology and financial elements, the development of urban digital finance has also been significantly improved. To further explore the impact of urban digital finance on urban low-carbon development, using the data of 281 cities in China from 2011 to 2019, this paper firstly evaluates the urban CCEP, and further empirically investigates how digital finance influences CCEP. The empirical results show that: (1) Digital finance significantly improves the urban CCEP, and after conducting robustness tests and addressing the endogeneity issue, the above conclusion is robust. (2) For the sub-indicators, there is a U-shaped relationship between the coverage breadth of digital finance and CCEP. Moreover, the improvement of usage depth and digital support services could promote CCEP. (3) The channel tests indicate that digital finance improves the CCEP mainly by promoting green technology innovation and the development of urban tertiary industry. Meantime, digital finance has a stronger impact on improving CCEP in cities with more developed traditional finance, and the positive effect is significant in non-old industrial base cities and a two-control zone. Finally, this paper puts forward relevant policy suggestions.

This paper attempts to reveal the impact and mechanisms of digital inclusive finance (DIF) on agricultural carbon emission performance (ACEP). Specifically, based on the provincial panel data in China from 2011 to 2020, a super slacks-based measure (Super SBM) model is applied to measure ACEP. The panel regression model and spatial regression model are used to empirically analyze the impact of DIF on ACEP and its mechanism. The results show that: (1) during the study period, China’s ACEP exhibited a continuous growth trend, and began to accelerate after 2017. The high-value agglomeration areas of ACEP shifted from the Huang-Huai-Hai plain and the Pearl River Delta to the coastal regions and the Yellow River basin, the provincial differences displayed an increasing trend from 2011 to 2020. (2) DIF was found to have a significant positive impact on ACEP. The main manifestation is that the development of the coverage breadth and depth of use of DIF helps to improve the ACEP. (3) The positive impact of DIF on ACEP had a significant spatial spillover effect, that is, it had a positive effect on the improvement of ACEP in the surrounding provinces. These empirical results can help policymakers better understand the contribution of DIF to low-carbon agriculture, and provide them with valuable information for the formulation of supportive policies.

The growth in carbon emissions poses a severe challenge to global sustainable development, making it imperative to explore the impacts of economic restructuring and technological progress on Carbon Emission Performance (CEP). However, existing studies often lack an integrated analysis of economic restructuring and technological progress, while giving limited attention to the indirect role of Environmental Regulation (ER). This study constructs a multidimensional theoretical framework, breaking down economic restructuring into four dimensions—industrial structure, factor input, ownership, and new-type urbanization (NTU), and refining technological progress into technological innovation and energy efficiency. It uncovers the complex interplay among CEP, economic restructuring, technological progress, and ER. The findings reveal critical insights: (1) industrial structure suppresses CEP, whereas adjustments in factor input and ownership structure significantly enhance it; (2) the relationship between NTU and CEP exhibits a non-linear pattern; (3) compared to the technological innovation, energy efficiency provide a more substantial boost to CEP; and (4) ER positively moderates the impacts of factor input, ownership structure, and NTU. Finally, the study proposes recommendations for holistic economic restructuring and diversified ERs.