Estimating strong point CO2 emissions by combining spaceborne IPDA lidar and HSRL

Abstract

Anthropogenic CO₂ emissions, particularly from strong point sources like power plants, play a crucial role in the increase of atmospheric CO₂ through a complex interaction with the natural carbon sinks. China successfully launched the Atmospheric Environment Monitoring Satellite (AEMS) loaded with integrated path differential absorption (IPDA) lidar and high-spectral-resolution lidar (HSRL) on April 16, 2022. This satellite is capable of simultaneously detecting atmospheric CO₂ and aerosols. Using AEMS data, we developed a point-source emission retrieval algorithm based on a modified three-dimensional Gaussian plume model and applied it to 12 satellite overpasses of major power plants. Compared with emissions reported by the U.S. Environmental Protection Agency (EPA), our retrievals exhibit an average relative deviation of 6.23 % in the validation cases, which represents a 31.63 % reduction in error compared to the traditional two-dimensional model-based method. In all cases, the estimated emissions exhibit strong agreement with EPA data (R = 0.84) and a low mean absolute error (MAE) of 6.1 kt/day. The analysis indicates that the uncertainty of the emission inversion results ranges from about 12 % to 21 %, with an average of 17.1 %. These results demonstrate the ability of the IPDA–HSRL synergy to accurately quantify point source CO₂ emissions, and can supplement and verify existing bottom-up inventory methods.