The wealth of earth observation data of both types, in situ and remote sensing, provides an increasing information stream to improve daily air quality forecasts. However, satellite-borne sensors in particular need special techniques for exploitation in data assimilation algorithms. R-EDA will develop and deliver improved data assimilation methods to assure optimal exploitation of observations. Both in situ and remote sensing in combination with participating regional chemistry transport models serve as the underlying data. The ability to provide analysed chemical fields along with locally and temporally resolved error estimates is a key objective, making use of a multi-model ensemble approach. Assimilated chemical constituents include all routinely measured species and particulate matter, irrespective of direct or indirect (e.g. tropospheric column or aerosol optical depth) data provision. The resulting analyses of the chemical state of the atmosphere are required to be chemically consistent, that is to preserve the integrity of natural balance within chemical families.