We perform global-scale inverse modeling to constrain present-day atmospheric mercury emissions and relevant physiochemical parameters in the GEOS-Chem chemical transport model. We use Bayesian inversion methods combining simulations with GEOS-Chem and groundbased Hg0 observations from regional monitoring networks and individual sites in recent years.
