No title
Monitoring atmospheric CO2 concentration changes across China is crucial for reducing carbon emissions and tackling global warming. Due to monitoring gap in satellite observations, this paper uses the Extremely Randomized Trees (ERT) model alongside OCO-2 satellite data and predictor variables to develop a 0.1° high-resolution monthly dataset of column-averaged dry air CO2 mole fraction (XCO2) in
