Abstract. A reliable quantification of greenhouse gas emissions is important for climate change mitigation strategies. Inverse methods based on observations and atmospheric transport simulations can support emission quantification at the national scale, yet, they are often limited by the observing systems, transport model uncertainties, and inversion methodologies. This two-part study introduces a system for observation-based, regional methane flux estimation. In the present Part 2, we apply this system to estimate German methane emissions in 2021. The numerical weather prediction model ICON with its ART module for trace gases is used to simulate the atmospheric transport while estimating uncertainties using a transport ensemble. We use a priori fluxes from national reporting to facilitate the validation of reported fluxes. Posterior fluxes are estimated with a modified synthesis inversion method introduced in Part 1, relying on in-situ observations. Compared to the a priori, we find a significant increase in methane emissions in Germany and in the Benelux. We estimate German methane emissions (32±19) % higher than the anthropogenic emissions in the national inventory, and our inversion method attributes this difference mainly to the agricultural sector, although separation from Land Use, Land Use Change and Forestry (LULUCF) as well as natural fluxes requires further research. The combination of an ensemble-enhanced numerical weather prediction model for atmospheric transport and good observation coverage paves the way to sector-specific, observation-based national emission estimates.
Bruch et al. (Mon,) studied this question.