Dataset of Near real-time inversion of high-resolution anthropogenic carbon emissions in the Pearl River Delta region based on the four-dimensional local ensemble transform Kalman filter

This study developed a kilometer-scale carbon assimilation system (the Guangzhou Regional Atmospheric Composition and Environment Forecasting System–Greenhouse Gas–Data Assimilation, GRACES-GHG-DA) by coupling the weather research and forecasting–greenhouse gas (WRF-GHG) model with the four-dimensional local ensemble transform Kalman filter (4D-LETKF). GRACES-GHG-DA generates a near-real-time 4-km anthropogenic emission inventory. The simulated CO2 concentration was constrained by seven greenhouse gas monitoring stations in the Pearl River Delta (PRD) region.Sources of meteorological fields and a priori sources included the FNL (Final) Operational Global Analysis data set ,the MOD09A1V6.1 product, the CO₂ concentration fields from the CarbonTracker products, and four anthropogenic CO₂ emission inventories(EDGAR V7.0 ,ODIAC v2023,GCP-GridFEDv2023.1 and MEICv2.0). The results of this study provide a robust scientific basis for advancing the dynamic updating and quantitative evaluation of anthropogenic emissions across meso- to microscale domains.