The overarching goal of this project is to constrain CO2 and CH4 emissions in the southeastern US from urban, biogenic, and oil-&-gas-related sources and sinks. Multiple state-of-the-art inverse modeling approaches will be used to assimilate a combination of in situ measurements from recent field campaigns (SENEX), NOAA flask measurements, and observations from tall towers. Correlations with co- measured species (NOy, SO2, and CO) will be used to provide additional constraints on greenhouse gas fluxes and for sector attribution. The transport histories of air masses sampled by SENEX flights will be simulated using a combination of Eulerian (GEOS- Chem and CMAQ) and Lagrangian (FLEXPART-WRF) transport models. SENEX observations will be assimilated using two variational inversions coupled with GEOS- Chem and FLEXPART-WRF and a probabilistic Bayesian Markov Chain Monte Carlo (MCMC) inversion incorporating these along with CMAQ. A thorough and systematic quantification of various uncertainties, including instrument errors, model transport errors, and errors in the prior information used will be achieved through a careful error analysis in each inversion system and an inter-comparison of the ensemble of inversions. The overall results will be validated against constraints from SEAC4RS, flask measurements, tall towers and CEMS power-plant emissions data.