Reducing carbon dioxide emissions in China's manufacturing industry: a dynamic vector autoregression approach

Currently, global warming, frequent occurrence of extreme weather and air pollution are common problems facing the international community. Carbon dioxide emissions are the root causes of these environmental and climate issues. Due to rapid industrialization and urbanization, China has become the world's largest energy consumer and carbon dioxide emitter. Moreover, the manufacturing industry is highly energy-consuming and pollution-intensive, accounting for nearly 60% of China's total energy consumption and over 50% of total carbon dioxide emissions. Thus, identifying the main drivers of the industry's carbon dioxide emissions is vital for China's emission reduction and global efforts to enhance environmental protection. This study uses Vector Autoregressive model to analyze the influencing factors of the changes in carbon dioxide emissions in the industry. The results show that energy efficiency plays a dominant role in reducing carbon dioxide emissions. Urbanization also has significant effect on carbon dioxide emissions because of large-scale real estate construction and high rate of vehicle ownership. Energy structure has higher impact on emission reduction than industrialization due to massive coal consumption and industrial structure optimization. Therefore, the Chinese government should increase investment in energy-saving technology, optimize energy structure, promote the production and use of new energy and hybrid vehicles.