Decomposition Analysis and Trend Prediction of CO2 Emissions in China’s Transportation Industry

Abstract

China’s transportation industry has become one of the major industries with rapid growth in CO2 emissions, which has a significant impact in controlling the increase of CO2 emissions. Therefore, it is extremely necessary to use a hybrid trend extrapolation model to project the future carbon dioxide emissions of China. On account of the Intergovernmental Panel on Climate Change (IPCC) inventory method of carbon accounting, this paper applied the Logarithmic Mean Divisia Index (LMDI) model to study the factors affected by CO2 emissions. The affected factors are further subdivided into the scale of employees, per capita carrying capacity, transport intensity, average transportation distance, energy input and output structure, energy intensity and industrial structure. The results are as follows: (1) Per capita carrying capacity is the most important factor to promote the growth of CO2 emissions, while industrial structure is the main reason to inhibit the growth of CO2 emissions; (2) the expansion of the number of employees has played a positive role in the growth of CO2 emissions and the organization and technology management of the transportation industry should be strengthened; (3) comprehensive transportation development strategy can make the transportation intensity effect effectively reduce CO2 emissions; (4) the CO2 emissions of the transportation industry will continue to increase during 2018–2025, with a cumulative value of about 336.11 million tons. The purpose of this study is to provide scientific guidance for the government’s emission reduction measures in the transportation industry. In addition, there are still some deficiencies in the study of its influencing factors in this paper and further improvements are necessary for the subsequent research expansion.