Direct Estimation of Global Anthropogenic CO ₂ Emissions Using Satellite Data

Reliable statistics on anthropogenic CO₂ emissions are fundamental for carbon cycle and climate change research. Satellite observations offer a potential objective and efficient alternative to the current self-reporting mechanism. However, the current satellite projects provide only column-averaged CO₂ amount (XCO₂) data. This paper proposes a direct estimation method based on satellite-based CO₂ column amount, different from the conventional “top-down” approaches, which usually adopt satellite-observed data as an indicator to disaggregate consumption statistics. Here, the monthly CO₂ emissions from 2010 to 2019 are estimated globally using CO₂ data retrieved from the Greenhouse Gases Observing Satellite. The geographically and temporally weighted regression model is adopted to account for local spatial and temporal variability. The enhanced XCO₂ data and the local wind speed, vertical velocity, air temperature, water vapor concentration, and fire emissions are included in the estimation process. The validation results of the newly derived CO₂ emissions strongly agree with the Open-source Data Inventory for Anthropogenic CO₂ data (R² = 0.929). This high global consistency demonstrates the great potential of direct estimation from satellites, with improved frequency and a broader coverage range.