SIMBAD is a simplified emission-concentration model based on CAMx, a multi-scale photochemical modelling system, and the Direct Decoupled Method. DDM is an algorithm developed for model sensitivity evaluation that computes first-order derivatives of concentration fields of a reference simulation with respect to multiple input parameters perturbations, such as precursors emissions, over each grid cell and each time step. SIMBAD can estimate the variation of daily average concentrations from the reference base case due to emission variations, therefore it can support decision makers in planning air quality policies considering both yearly mean concentrations as well as number of exceedances of a daily threshold. In this study SIMBAD has been validated for the reconstruction of PM concentrations using three emission reduction scenarios. The behaviour of SIMBAD and CAMx has been investigated both in situations showing a rather linear relationship between emission and concentration variations, and in more complex scenarios, where different precursors and sectors are involved, and the nonlinear nature of the atmospheric chemistry processes are more relevant. SIMBAD performances have been evaluated in four urban sites, showing good results in reproducing PM daily average concentrations and limit value exceedances. In general, SIMBAD tends to slightly underestimate CAMx values, therefore the validation of the number of exceedances reduction compared to the basecase shows a moderate overestimation by SIMBAD (+ 11%).