Synthetic observations, emission sensitivity, and inversed emission datasets

In this study, we developed a new inverse framework, in which the atmospheric concentration of gases was decomposed into two parts: “enhancement” caused by emissions during the study period and “background” from decay of initial conditions. This inversion framework consists of a 3D CTM to simulate the emissions sensitivity for reference species, an Interspecies Emission Sensitivity Conversion (IESC) module to calculate emission sensitivity for any target species from that of the reference species, and a 2D box model to simulate the decay of initial conditions. This inversion framework eliminates the need to run 3D CTM for each target species, thereby significantly reducing computational costs compared to traditional approaches. We tested this inversion system using observing system simulation experiments on reference species (CH₄) and six target species (SF₆, H-1301, HCFC-141b, CH₃CCl₃, HCFC-132b, and HFC-152a), and found it performed well for long-lived gases. This new inversion method can help scientists and policymakers better monitor emissions at global and continental scales, while saving significant computing time and resources.