Can structure optimization of mining industry reduce carbon emission in China? Evidence from kernel density estimation and PVAR approach

Abstract

Abstract The mining sector, a significant component of the economy, is under intense pressure to cut carbon emissions in order to help China meet its targets of "carbon peaking" by 2030 and "carbon neutrality" before 2060. Mining carbon emissions are significantly influenced by technical advancement and mining activity intensity. The effect of mining industry industrial structure and energy structure on mining industry carbon emissions, however, has not yet been explored. Therefore, this study aimed to explore the association between the mining structure and carbon emissions. Kernel density estimation was used to analyze the dynamic evolution of mining industry carbon emission intensity in China and the eastern, central, and western regions; a Panel-VAR model was used to analyze the factors impacting the carbon emission intensity of the mining industry. Results revealed different downward trends in carbon emission intensity in China and the eastern and central regions, with the most obvious decline in mining industry emission intensity in the economically developed eastern region. At the national level, the percentage of large and medium-sized mines, the average production of individual mines, and the energy consumption structure of the mining industry are the key factors affecting the carbon emission intensity of the mining industry, but the degree of influence of these factors varies among different regions of China. Based on the findings, comprehensive policy recommendations are made to reduce carbon emissions in the Chinese mining industry.