As one of the most influential greenhouse gases, carbon dioxide (CO₂) has a profound impact on the global climate. The spaceborne integrated path differential absorption (IPDA) lidar will be a great sensor to obtain the columnar concentration of CO₂ with high precision. This paper analyzes the performance of a spaceborne IPDA lidar, which is part of the Aerosol and Carbon Detection Lidar (ACDL) developed in China. The line-by-bine radiative transfer model was used to calculate the absorption spectra of CO₂ and H₂O. The laser transmission process was simulated and analyzed. The sources of random and systematic errors of IPDA lidar were quantitatively analyzed. The total systematic errors are 0.589 ppm. Monthly mean global distribution of relative random errors (RREs) was mapped based on the dataset in September 2016. Afterwards, the seasonal variations of the global distribution of RREs were studied. The global distribution of pseudo satellite measurements for a 16-day orbit repeat cycle showed relatively uniform distribution over the land of the northern hemisphere. The results demonstrated that 61.24% of the global RREs were smaller than 0.25%, or about 1 ppm, while 2.76% of the results were larger than 0.75%. The statistics reveal the future performance of the spaceborne IPDA lidar.

China is developing the High-precision Greenhouse gases Monitoring Satellite (HGMS), carrying a high-spectral-resolution lidar (HSRL) for aerosol vertical profiles and imaging grating spectrometers for CO₂ measurements at the same time. By providing simultaneous evaluation of the aerosol scattering effect, HGMS would reduce the bias of the XCO₂ retrievals from the passive sensor. In this work, we propose a method to reduce aerosol-induced bias in XCO₂ retrievals for the future HGMS mission based on the correlation analysis among simulated radiance, XCO₂ bias, and aerosol optical depth (AOD) ratio. We exercise the method with the Orbiting Carbon Observatory-2 (OCO-2) XCO₂ retrievals and AOD ratio inferred from the OCO-2 O₂ A-band aerosol parameters at 755 nm and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD at 532 nm at several Total Carbon Column Observing Network (TCCON) sites in Europe. The results showed that 80% of measurements from OCO-2 were improved, and data from six TCCON sites show an average of 2.6 ppm reduction in mean bias and a 68% improvement in accuracy. We demonstrate the advantage of fused active–passive observation of the HGMS for more accurate global XCO₂ measurements in the future.