Emission rate and chemical state estimation by 4-dimensional variational inversion H. Elbern1, A. Strunk1, H. Schmidt1,*, and O. Talagrand2 1Rhenish Institute for Environmental Research at the University of Cologne, Köln, Germany 2Laboratoire de Meteorologie Dynamique, Paris, France *now at: Max-Planck-Institute for Meteorology, Hamburg, Germany
Abstract. This study aims to assess the potential and limits of
an advanced inversion method to estimate pollutant
precursor sources mainly
from observations. Ozone, sulphur dioxide,
and partly nitrogen oxides observations are taken to infer source
As methodology, the four-dimensional variational data assimilation
has been generalised and employed to include emission rate
optimisation, in addition to
chemical state estimates as usual objective of data assimilation.
To this end, the optimisation space of the
variational assimilation system has been complemented by emission rate
correction factors of 19 emitted species at each emitting grid
point, involving the University of Cologne mesoscale EURAD
For validation, predictive skills
were assessed for an August 1997 ozone episode,
comparing forecast performances of
pure initial value optimisation, pure emission rate
optimisation, and joint emission rate/initial value optimisation.
Validation procedures rest on both measurements withheld from data
assimilation and prediction skill evaluation of
forecasts after the inversion procedures.
Results show that excellent
improvements can be claimed for sulphur dioxide forecasts, after
emission rate optimisation. Significant improvements can be claimed
for ozone forecasts
after initial value and joint emission rate/initial value
optimisation of precursor constituents. The additional benefits
emission rate/initial value optimisation are moderate, and very
typical cases, where upwind emission rate optimisation is
essential. In consequence of the coarse horizontal model grid resolution of 54 km, applied in this study,
comparisons indicate that the inversion improvements can rest on
assimilating ozone observations only, as the inclusion of NOx
observations does not provide additional forecast skill.
Emission estimates were found to be largely independent from initial
guesses from emission inventories, demonstrating the potential of the
4D-var method to infer emission rate improvements. The study also
points to the need for improved horizontal model resolution to more
efficient use of NOx observations.
Citation: Elbern, H., Strunk, A., Schmidt, H., and Talagrand, O.: Emission rate and chemical state estimation by 4-dimensional variational inversion, Atmos. Chem. Phys., 7, 3749-3769, doi:10.5194/acp-7-3749-2007, 2007.