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Transportation carbon emission reduction has become an important driving point for China to achieve carbon peak and carbon neutrality. Based on the three-dimensional grey correlation analysis model, taking the five factors affecting transportation carbon emissions, namely, population, GDP, tertiary industry, energy structure and logistics scale, as the research object, the transportation carbon emissions of China’s low-carbon pilot and nonpilot provinces from 2010 to 2019 are calculated based on the Intergovernmental Panel on Climate Change (IPCC) carbon emission accounting method. The time series grey correlation degree and regional grey correlation degree of each influencing factor and traffic carbon emission are obtained using the provincial data, so as to provide policy suggestions for China to achieve the goal of “carbon peak and carbon neutrality” in the field of transportation. The results show that the descending order of the five influencing factors on transportation carbon emissions is: energy structure, logistics scale, population, GDP and tertiary industry. From 2010 to 2019, the time series grey correlation degree between the five influencing factors and transportation carbon emissions shows a fluctuating downward trend, but the impact of demographic factors has become more and more obvious in the past two years; According to the difference of grey correlation degree in different regions, the traffic development of various provinces in China is different, so it is necessary to formulate relevant policies individually.
Sun et al. (Fri,) studied this question.