Assessing CO2 emissions in China's iron and steel industry: A dynamic vector autoregression model

作者：Xu, Bin; Lin, Boqiang^*

来源：Applied Energy, 2016, 161: 375-386.

DOI：10.1016/j.apenergy.2015.10.039

• Iron and steel industry
• Carbon dioxide emissions
• Vector autoregression model

Energy saving and carbon dioxide emission reduction in China is attracting increasing attention worldwide. At present, China is in the phase of rapid urbanization and industrialization, which is characterized by rapid growth of energy consumption and carbon dioxide (CO2) emissions. China's steel industry is highly energy-consuming and pollution-intensive. Between 1980 and 2013, the carbon dioxide emissions in China's steel industry increased approximately 11 times, with an average annual growth rate of 8%. Identifying the drivers of carbon dioxide emissions in the iron and steel industry is vital for developing effective environmental policies. 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 CO2 emissions because of mass urban infrastructure and real estate construction. Economic growth has more impact on emission reduction than industrialization due to the massive fixed asset investment and industrial energy optimization. These findings are important for the relevant authorities in China in developing appropriate energy policy and planning for the iron and steel industry.

• 出版日期2016-1-1
• 单位闽江学院; 江西财经大学; 厦门大学