Dataset of 3km FFCO2 emission of the Guangdong-Hong Kong-Macao Greater Bay Area from 2000 to 2018

In the context of technical barriers to the use of satellite carbon observations for regional emission reduction, global-scale high-resolution inventories of fossil fuel carbon dioxide (FFCO2) emissions have become the main data source for regional FFCO2 emission studies, however, there are still significant uncertainties in the use of existing global-scale FFCO2 emission inventories for regional studies. To this end, this study Quantitative analysis three global-scale high-resolution FFCO2 emission inventories (ODIAC 2020b, EDGAR v6.0, PKU-CO2-v2) for regional-scale studies of heterogeneity and variability, then, based on the Kalman filter, the features of the three sets of data are fused. New data from the Kalman filter reconstructed long-term series 2000-2018 show that the uncertainty of Kalman filter fusion results has decreased from ± 15% -20% to ± 10%.