This study presents a new inverse modeling framework that assimilates information from both ground-based and satellite CO2 observations to constrain urban carbon emissions over Seoul. While multiple studies have looked at using either ground-based or satellite observations to constrain urban emissions, this approach aims to optimally combine the information from the two within a common inverse modeling framework. This framework, if robust and scalable, can be deployed for multiple other urban areas and megacities. In that sense, this study sets an important benchmark for future studies aiming to combine ground-based and satellite data for constraining urban emissions, and highly relevant and timely for the global carbon cycle community.