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Modelling of aerosol particles with chemical\udtransport models is still based mainly on static emission\uddatabases while episodic emissions cannot be treated sufficiently. To overcome this situation, a coupling of chemical\udmass concentration modelling with satellite-based measurements relying on physical and optical principles has been developed. This study deals with the observation operator for a component-wise assimilation of satellite measurements.\udIt treats aerosol particles classified into water soluble,\udwater insoluble, soot, sea salt and mineral dust containing\udaerosol particles in the atmospheric boundary layer\udas separately assimilated aerosol components. It builds on\uda mapping of aerosol classes used both in observation and\udmodel space taking their optical and chemical properties\udinto account. Refractive indices for primary organic carbon\udparticles, anthropogenic particles, and secondary organic\udspecies have been defined based on a literature review.\udTogether with a treatment of different size distributions\udin observations and model state, this allows transforming\udthe background from mass concentrations into aerosol\udoptical depths. A two-dimensional, variational assimilation\udis applied for component-wise aerosol optical depths. Error\udcovariance matrices are defined based on a validation\udagainst AERONET sun photometer measurements. Analysis\udfields are assessed threefold: (1) through validation against\udAERONET especially in Saharan dust outbreak situations,\ud(2) through comparison with the British Black Smoke and\udSulphur Dioxide Network for soot-containing particles, and\ud(3) through comparison with measurements of the water soluble components SO4, NH4, and NO3 conducted by the\udEMEP (European Monitoring and Evaluation Programme)\udnetwork. Separately, for the water soluble, the soot and the\udmineral dust aerosol components a bias reduction and subsequent a root mean square error reduction is observed in the analysis for a test period from July to November 2003. Additionally, examples of an improved analysis during wildfire\udand dust outbreak situations are shown

Observation operator for the assimilation of aerosol type resolving satellite measurements into a chemical transport model