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High-energy consumption and high-emission industries contribute a lot to economic development, but their carbon emissions are also huge. In order to achieve the dual-carbon target as early as possible, it is necessary to reduce the carbon emissions of high-energy consumption and high-emission industries. This paper selected five representative factors (population, per capita gross domestic product (GDP), energy intensity, energy structure and carbon emission coefficient) and adopted the logarithmic mean divisia index (LMDI) method to decompose the driving factors of carbon emissions. Therefore, this paper uses Tapio decoupling model to analyze the decoupling relationship between the two factors with the greatest impact on carbon emissions and carbon emissions. The results show that: (i) There is a good decoupling between high-energy consumption and high-emission industries and per capita GDP, and the impact of per capita GDP on carbon emissions will gradually decrease in the future; (ii) The decoupling relationship between carbon emissions and energy intensity is poor. For some industries, the reduction of energy intensity can help reduce carbon emissions. Finally, this paper puts forward some suggestions to promote carbon emission reduction. This paper provides theoretical support for studying how to reduce carbon emissions and formulate relevant emission reduction policies in the high-energy consumption and high-emission industries. [ABSTRACT FROM AUTHOR]

In the last 20 years, China's steel production has proliferated, leading to increased environmental damage by releasing 574,000 tons of sulfur dioxide (SO2), 1,114,000 tons of nitrogen oxide (NOx), and 897,000 tons of particulate matter (PM) in 2020; therefore, the country is now struggling to reduce carbon emissions and tackle climate change because of the conflicting demands of economic growth and environmental protection. Given the global emphasis on decarbonization and sustainable production, China has prioritized achieving peak carbon emissions of 30% by 2030 and carbon neutrality by 2060. Likewise, China's steel industry is progressing toward attaining the maximum carbon dioxide (CO2) emissions by 2025. This study reveals that despite a 321 Mt increase in global energy-related CO2 emissions in 2022, CO2 emissions in China experienced a decline of 230 Mt during the same period. Notwithstanding enacting several pertinent statutes and directives, China's iron and steel sector has not advanced substantially. [ABSTRACT FROM AUTHOR]

Identifying the differentiated effects of different environmental regulations is the basis for promoting China's zero carbon emissions and carbon neutrality. We used Chinese provincial panel data from 2003 to 2017 to empirically test the impact of different environmental regulations on carbon neutrality through spatial measurement models. The highlights of the study are as follows: (1) Environmental regulations exert significant impact on carbon emissions, but different types of environmental regulations exert significantly different effect on carbon emissions. Public participation environmental regulation has a control effect on regional carbon emissions, while command-based and market-based environmental regulations had no significant effect on regional carbon neutrality. (2) The heterogeneity of the impact of different types of environmental regulations on carbon emissions can also be identified from the regional impacts heterogeneity and lags impact heterogeneity. (3) The combined mandatory and market-based environmental regulations and the combined mandatory and public-participatory environmental regulations significantly inhibited regional carbon neutrality. [ABSTRACT FROM AUTHOR]

A scientific assessment of the synergistic effect of the low-carbon city pilot policy in reducing air pollution and carbon emissions is needed to promote carbon peak and carbon neutrality. This study applied the Spatial Durbin Model-Difference in Difference technique to investigate the synergistic effect of air pollution and carbon emission reduction through the implementation of the low-carbon city pilot policy. The main results are as follows. (1) A spatial phenomenon was observed, in which there was a coexistence of urban carbon emissions and air pollution agglomerations. The spatial characteristics of the "symbiotic" carbon emissions and air pollution agglomerations were revealed. (2) The low-carbon city policy significantly reduced CO2, SO2, and PM2.5 concentrations, and the effect of the "co-governance" of air pollution and carbon emission reduction was obvious. (3) There was a clear regional heterogeneity in the synergistic effect of air pollution and carbon emission reduction in low-carbon cities. A stronger incentive effect was apparent in central and western cities, resource-based cities, and key environmental protection cities. (4) To achieve a synergistic governance "sharing" situation, the transmission mechanism of the low-carbon city pilot policy was the reduction of total energy consumption, the promotion of industrial restructuring, the optimization of the factor endowment structure, and the continuous improvement of the urban transport structure and green innovation. Our results not only help advance the research on synergistic reduction of air pollution and carbon emissions, but also can be of interest to low-carbon city policy makers in China. [ABSTRACT FROM AUTHOR]

Environmental degradation has been recognized as a global issue due to high energy consumption and economic growth. This situation needs researchers to focus on, thereby, the current article examined the impact of renewable energy production (REP), energy import, renewable energy consumption (REC), gross domestic product (GDP), inflation, and foreign direct investment (FDI) on the carbon dioxide (CO2) emission in China. The study considered secondary data and extracted it from the World Bank database covering the period 1981 to 2018. The current article has examined the stationarity of the constructs using Augmented Dickey-Fuller tests and investigated the association among constructs using the quantile autoregressive distributed lag (QARDL) model. The data revealed that REP, energy import, and REC, had a significant and negative linkage with CO2 emission in China. In contrast, GDP, inflation, and FDI are linked with CO2 emission in a positive manner. The article also guided the policymakers regarding the policy development related to reducing carbon emissions using renewable energy production and consumption. [ABSTRACT FROM AUTHOR]