Improving federal German emission inventories by inverse modelling
Complying with international commitments (Gothenburg protocol of the Convention on Long-Range Transboundary Air Pollution), emissions of reactive trace gases and aerosols are subject to annual estimations by national authorities, as they cannot be measured directly. Yet, combining atmospheric chemistry models with measurements of air quality monitoring networks and trace gas and aerosol retrievals of remote sensing observations from space borne platforms has the potential to improve emission inventories by advanced spatio-temporal inverse modelling techniques.
In this project the 4-dimensional variational data assimilation method is selected, based on the forward and adjoint EURopean Air pollution Dispersion - Inverse Model (EURAD-IM) with its capability to model grid resolved emission optimisation (Elbern et al., 2007). The main objective of this research project is to investigate the potential and limits of regional observation networks to allow for emission corrections on a SNAP (Selected Nomenclature for sources of Air Pollution) basis.