BASIC: A Boosted Aerosol-Size-Integrated XCO2 Retrieval Algorithm

Accurate retrieval of the dry-air mole fraction of CO₂ (XCO₂) is essential for tracking emissions and supporting mitigation. However, aerosols significantly alter photon path lengths through scattering and absorption, making them the largest variable error source in XCO₂ retrieval. Current efforts to improve aerosol treatment in XCO₂ retrievals, such as the Atmospheric CO₂ Observations from Space (ACOS) algorithm for the Orbiting Carbon Observatory-2 (OCO-2), primarily focus on enhancing prior estimates of aerosol optical depth (AOD), vertical distribution, and optical properties. Yet, aerosol particle size distribution (PSD) parameters—a critical microphysical factor contributing to nonlinear variations in aerosol optical properties—are held fixed and excluded from the ACOS retrieval, thereby introducing additional biases into the XCO₂ results.

To address this challenge, we developed a Boosted Aerosol-Size-Integrated XCO₂ (BASIC) retrieval algorithm that concurrently retrieves XCO₂ and aerosol PSD parameters from OCO-2 observations. Validation at five Total Carbon Column Observing Network (TCCON) sites in East Asia shows that BASIC reduces the root-mean-square error (RMSE) by 30% and 13% compared to the standard and bias-corrected OCO-2 products, respectively. The improvement primarily stems from BASIC’s ability to generate forward-modeled spectra that more closely match observations than those from ACOS, particularly in the O₂ A-band, which is highly sensitive to aerosols. These results highlight the importance of incorporating variable aerosol PSD in retrievals and demonstrate that BASIC more accurately represents aerosol effects on radiative transfer. Our findings suggest that PSD-aware retrievals can significantly improve the accuracy of satellite-derived XCO₂ estimates under highly variable aerosol loading conditions, such as those in East Asia.