Direct Estimation of Global Anthropogenic CO2 Emissions Using Satellite Data
Abstract. 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.
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