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This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Excessive energy-related carbon emission intensity will lead to deterioration of environmental quality and hinder green economic growth. This paper proposes a novel self-adaptive fractional order grey generalized Verhulst model (SAFGGVM) to predict energy-related carbon emission intensity in China, America, India, Russia, and Japan with nonlinear and complex characteristics effectively. Firstly, self-adaptive fractional order and dynamic background value coefficient are introduced to capture the nonlinear evolutionary trends. Subsequently, the optimal nonlinear parameters are determined using Grey Wolf Optimization algorithm through comprehensive comparison. Furthermore, the flexibility of SAFGGVM is verified by presenting its relevance to existing models. Finally, the validity, applicability, and robustness of SAFGGVM are confirmed by comparing with two machine learning models and four grey prediction models. The empirical results exhibit that the overall precision of SAFGGVM model significantly prevails over the others in five cases, with MAPE values less than 6% in both the simulation and prediction intervals. The out-of-sample forecast results indicate that the energy-related carbon emission intensity of five countries will fall into 5.7024, 1.6030, 7.3668, 8.1633, 2.0399 tons/10,000 USD by 2025, and the decreasing rate of developing countries tends to catch up with, or even exceed, developed countries. Projection results can serve as a reference point for countries to achieve green and sustainable development. • A novel self-adaptive grey generalized Verhulst model is proposed. • Energy-related carbon emission intensity (ECEI) of five countries is predicted. • Optimal nonlinear parameters are determined by Grey Wolf Optimization algorithm. • The novel model is superior to other competing models in accuracy and roubutness. • Decline rate of ECEI in developing countries will catch up with developed countries. [ABSTRACT FROM AUTHOR]

Carbon emissions (CE) have a profound impact on the natural environment of the surface, and the ecologic environment quality (EEQ) affects the conversion and absorption of CE. CE and EEQ have an interaction and mutual influence relationship. The connection between them includes not only local interactions but also the long-range distance of external systems. It is critical to measure CE and EEQ and coordinate their association in order to increase the effectiveness of CE and EEQ collaborative governance. However, the traditional remote sensing ecological index (RSEI) model ignores the importance of air quality. Furthermore, there is limited current research on the local and telecoupling relationship between CE and the EEQ. To fill these research gaps, this paper first used night light data to dynamically monitor CE. Then we proposed an upgraded RSEI model (RSEInew) to assess EEQ. Finally, the local and telecoupling coordination degree (LTCCD) model was suggested to further investigate their relationship in the Yangtze River Economic Belt (YREB) from 2000 to 2019. The results showed that: (1) Total CE in the YREB increased from 837.5738 million tons to 4757.3794 million tons between 2000 and 2019 but has not yet reached its peak. Jiangsu and Zhejiang are at the forefront in terms of CE and have huge emission reduction potential. (2) The YREB's overall EEQ has deteriorated over the last 20 years. The average RSEInew value ranged between 0.52 and 0.71, with "medium" and "good" EEQ levels dominating. (3) The LTCCD of CE and EEQ in the YREB has increased year by year. This study can deliver a reference for decision-makers to synergistically formulate carbon emission reduction plans and environmental protection schemes. • Ecologic environment quality should combine regional characteristics, our RSEInew model could evaluate it with introduces PM2.5. • Carbon emissions and the ecologic environment quality interact with each other, with near- and long-range interactions. • The LTCCD model enable to analysis the local and telecoupling relationships of CE and EEQ. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the "carbon peaking and carbon neutrality" goal. [Display omitted] • Evaluation system of Balanced Green Development Index is constructed. • The system was applied to balance green economic growth with environmental equity. • Emission trading scheme has significantly improved the level of balanced green development. • The promotion effect is more obvious in western China. [ABSTRACT FROM AUTHOR]

In the social context of enhancing environmental quality and mitigating climate change, the improvement of carbon emission efficiency has emerged as a hot topic recently due to its promise as an approach to reduce emissions and improve environmental quality. A large volume of studies has identified technological progress as a critical factor affecting energy efficiency and pollution emission levels. From the perspective of national differences, the contributions of our study lied in constructing a system to measure technological progress based on the outputs and transformations of a country's technical progress level. Secondly, this paper examined the direct effect of technological progress on carbon emission efficiency, and the interaction effect between technological progress and energy intensity on carbon emission efficiency. Thirdly, we taking into account differences in the effect that technological progress can have on carbon emission efficiency in different national contexts. For this purpose, we evaluated the carbon emission efficiency of 59 countries in the period 1998–2016 using a super-SBM model, subsequently employing a national panel quantile regression method to explore the multiple effects of technological progress on the carbon emission efficiency of countries with different levels of efficiency. Our main findings indicate that the national carbon emission efficiency steadily increased across the study period, albeit with slight fluctuations, and that generally countries' carbon emission efficiency still exists great potential of enhancement. Technological progress will drive carbon emission efficiency to improve significantly, while this effect varies between countries with different levels of efficiency. Further, the interaction effects of technological progress and energy intensity are shown to exert complex effects on carbon emission efficiency, providing evidence that scientific and technological achievements need to be converted into productivity in time to offset the negative environmental effects of pollution and emissions. Governmental departments should, as a result, strengthen environmental supervision and urge enterprises to eliminate backward production capacity, introduce new technologies, and improve energy efficiency. Countries may realize the development of low-carbon sustainable societies by transforming their economic growth mode and adopting energy-saving production techniques. [ABSTRACT FROM AUTHOR]