Identification of on-road vehicle CO2 emission pattern in China: A study based on a high-resolution emission inventory

Abstract

As the country with the largest anthropogenic CO2 emission, China is greatly influential on fighting with climate change. However, CO2 emitted from on-road vehicles in China is a barrier to its carbon neutral due to the inevitable increase trend of vehicle quantity. Thus, to meet the requirement of refined policy-making for vehicular CO2 abatement, we calculated the CO2 emissions from 37 vehicular types and 3 fuel categories across 339 cities in China through the bottom-up method, and developed a national vehicular CO2 emission inventory in a high spatial resolution (1 km × 1 km). Additionally, machine learnings were conducted to the inventory for the emission pattern identification. It was found that the total vehicular CO2 emission in 2019 was 1090 million tons, and 77.1% of CO2 was emitted by vehicles of light-duty gasoline vehicle (LDGV) and heavy-duty diesel truck (HDDT). In addition, for the grids accompanying CO2 emissions, 75% of vehicular CO2 emissions were contributed by 15% of grids (hot grids). Furthermore, results of machine learning showed that LDGVs mainly distributed in economically advanced regions of which vehicular structures were relatively simple, while HDDTs were widely applied on the national scale. Based on the results above, two measures were proposed: (1) Electric cars have to be strongly promoted in hot grids for the LDGV replacement. (2) Long-distance freight tool replacements are urgently required in the national wide. Our study provided a studying base for further investigations on decarbonization and a new insight of China's vehicular CO2 emission controls.