Evaluating anthropogenic CO2 emissions of China estimated from atmospheric inversions of “proxy” species against ground CO2 measurements

Accurate estimation of anthropogenic CO₂ emissions (ACE) is of great importance for climate change mitigation, however, it is quite challenging.  Co-emitted gases, e.g. CO and NO_x, have been reported to be useful for tracking ACE. Here we estimated ACE of China based on “proxy” species (i.e. CO and NO_x) inversions with emission ratios of CO₂ and the “proxy” species and evaluated the estimates using ground CO₂ measurements of three tower stations in population-dense areas based on the Stochastic Time-Inverted Lagrangian Transport (STILT) modeling driven by the Global Data Assimilation System (GDAS) meteorology. An ensemble of ACE of China were estimated from different combinations of anthropogenic CO or NO_x flux estimates and emission ratios, where the CO or NO_x fluxes were estimated from in-situ measured concentration data or satellite column concentration data, and the emission ratios were derived from two emission inventory datasets, i.e. multi-resolution emission inventory for China (MEIC) and Peking University global emission inventories (PKU-FUEL). We found all CO₂ simulations with “proxy” based ACE estimates (either using in-situ or satellite data) in one year clearly fitted better to observations than those with inventory datasets did, especially during winter and early spring. Meanwhile, large mismatches between simulations and observations were found for some periods, which indicated the use of CO or NO_x to track ACE may be not suitable for a whole year. Our preliminary result demonstrates the potential to use atmospheric “proxy” species to track anthropogenic CO₂ emissions in China.