The integration of satellite aerosol optical depth (AOD) and trace gas observations using data assimilation has the potential to improve our understanding of aerosol composition. This study evaluates these synergistic effects through combined constraints on total aerosols by AOD and on secondary aerosol formation by trace gases. The simultaneous data assimilation (DA) of NO<sub>2</sub>, SO<sub>2</sub>, CO, and HNO<sub>3</sub> from OMI, TROPOMI, MOPITT, and MLS, together with AOD from MODIS and VIIRS, improved aerosol analyses in most cases compared to conventional DA runs that separately assimilate AOD or trace gases satellite observations. Validation against independent surface observations of sulfate, nitrate, and ammonium (SNA), and PM<sub>2.5</sub> showed improved agreements by 6–98 % compared to the conventional DA runs and the control simulation without any data assimilation. Notably, the reduction in PM<sub>2.5</sub> model biases exceeded that achieved by the conventional DA of AOD by 56 % in Northeast Asia. These improvements were achieved by reduced SO<sub>2</sub> and soil dust emissions by 30 % and 60 % globally and increased NO<sub>x</sub> and carbonaceous aerosol emissions by 30 % and 15 %. The simultaneous DA provides even larger reductions in SNA and AOD biases by up to 25 % and 48 % respectively, when the current generation instruments (TROPOMI and VIIRS) is used, instead of the previous generation instruments (OMI and MODIS). This coupled aerosol and trace gas DA framework offers significant advantages for improving global aerosol composition analyses, informing policy decisions with co-benefits for air quality and climate, and optimizing the use of the current satellite observing network.