Methane (CH 4 ) is the primary component of natural gas and has a larger global warming potential than CO 2 . Recent top-down studies based on observations showed CH 4 emissions in California’s South Coast Air Basin (SoCAB) were greater than those expected from population-apportioned bottom-up state inventories. In this study, we quantify CH 4 emissions with an advanced mesoscale inverse modeling system at a resolution of 8 km × 8 km, using aircraft measurements in the SoCAB during the 2010 Nexus of Air Quality and Climate Change campaign to constrain the inversion. To simulate atmospheric transport, we use the FLEXible PARTicle-Weather Research and Forecasting (FLEXPART-WRF) Lagrangian particle dispersion model driven by three configurations of the Weather Research and Forecasting (WRF) mesoscale model. We determine surface fluxes of CH 4 using a Bayesian least squares method in a four-dimensional inversion. Simulated CH 4 concentrations with the posterior emission inventory achieve much better correlations with the measurements (R 2 = 0.7) than using the prior inventory (U.S. Environmental Protection Agency’s National Emission Inventory 2005, R 2 = 0.5). The emission estimates for CH 4 in the posterior, 46.3 ± 9.2 Mg CH4 /h, are consistent with published observation-based estimates. Changes in the spatial distribution of CH4 emissions in the SoCAB between the prior and posterior inventories are discussed. Missing or underestimated emissions from dairies, the oil/gas system, and landfills in the SoCAB seem to explain the differences between the prior and posterior inventories. We estimate that dairies contributed 5.9 ± 1.7 Mg CH 4 /h and the two sectors of oil and gas industries (production and downstream) and landfills together contributed 39.6 ± 8.1Mg CH 4 /h in the SoCAB.