Four-dimensional variational data assimilation allows for the simultaneous optimisation of initial values and emission rates by using trace-gas profiles from drone observations in a regional air quality model. Assimilated profiles positively impact the representation of air pollutants in the model by improving their vertical distribution and ground-level concentrations. This case study highlights the potential of drone data to enhance air quality analyses including local emission evaluation.