High-resolution spatio-temporal estimation of CO2 emissions from China's civil aviation industry

Emissions of carbon dioxide (CO2), as for different sectors have drawn increasingly attentions due to carbon peaking and neutrality goals. In the transportation sector, civil aviation industry is an important emission source. In this study, we proposed a technical framework to accurately estimate high-resolution spatio-temporal CO2 emissions from all the domestic flights within the Chinese mainland. In this solution, both quick access recorder (QAR) and flight schedule data were adopted. The QAR data provide the details of fuel consumptions during a flight and is used to train an accurate estimation model, while the flight schedule data enable us to estimate large scale CO2 emissions with both spatial and temporal details. With this technical framework, we calculated the total, yearly, monthly and daily CO2 emissions of domestic civil aviation industry within Chinese mainland from 2018 to 2021, with a spatial resolution up to 0.1 degrees x 0.1 degrees x 1000feet. The results have been validated with uncertainty analysis and comparison to the data provided by CarbonMonitor, and acquired apparent advantages in spatio-temporal accuracies and interpretabilities.