31 May 2023
 | 31 May 2023
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

European CH4 inversions with ICON-ART coupled to CarbonTracker Data Assimilation Shell

Michael Steiner, Wouter Peters, Ingrid Luijkx, Stephan Henne, Huilin Chen, Samuel Hammer, and Dominik Brunner

Abstract. We present the first application of the atmospheric chemistry and transport model ICON-ART in inverse modelling of greenhouse gas fluxes with an Ensemble Kalman Filter. For this purpose, we extended ICON-ART to efficiently handle gridded emissions, generate an ensemble of perturbed emissions during runtime, and use nudging on selected variables to keep the simulations close to analyzed meteorology. We show that the system can optimize total and source sector specific anthropogenic European CH4 fluxes on a national-scale in an idealized setup using pseudo-observations from a realistic network of measurement stations. We successfully estimated fluxes for agricultural emissions and partially for waste emissions, but were unable to constrain the sum of the remaining emission sources of comparatively low magnitude (mostly fugitives as well as emissions from industry and traffic). Also regions with low emissions and regions with low observational coverage could not be optimized individually for lack of observational constraints. Furthermore, we investigated the sensitivities towards different inversion parameters and design choices with 16 sensitivity runs using the same idealized setup, demonstrating the robustness of the approach when regarding some minimal requirements of the setup (e.g., number of ensemble members). Subsequently, we applied the system to real in-situ observations from 28 European stations for three years, 2008, 2013 and 2018. We used a priori anthropogenic fluxes from the EDGARv6 inventory and a priori natural fluxes from peatlands and mineral soils, inland waters, the ocean, biofuels and biomass burning and geology. Our results for the year 2018 indicate that anthropogenic emissions may be underestimated in EDGARv6 by ca. 25 % in the Benelux countries and, to a smaller degree, in northwestern France and southern England. In the rest of the domain, anthropogenic fluxes are corrected downwards by the inversion suggesting an overestimation in the a priori. For most countries, this means that the a posteriori country-total anthropogenic emissions are closer to the values reported to the United Nations Framework Convention on Climate Change (UNFCCC) than the a priori emissions from EDGARv6. Aggregating the a posteriori emissions across the EU27 + UK results in a total of 17.4 Tg yr−1, while the a priori emissions were 19.9 Tg yr−1. Our a posteriori is close to the total reported to UNFCCC of 17.8 Tg yr−1. Natural emissions are reduced from their a priori magnitude almost everywhere, especially over Italy and Romania/Moldova, where a priori geological emissions are high, and over the United Kingdom and Scandinavia where emissions from peatlands and wetlands were possibly unusually low during the hot and dry summer 2018. Our a posteriori anthropogenic emissions for the EU27 + UK fall within the range estimated by global top-down studies, but are lower than most other regional inversions. However, many of these studies have used observations from different measurement stations or satellite observations. The spatial pattern of the emission increments in our results, especially the increase in the Benelux countries, also agrees well with other regional inversions.

Michael Steiner et al.

Status: open (until 03 Oct 2023)

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  • RC1: 'Comment on egusphere-2023-853', Anonymous Referee #1, 26 Jun 2023 reply

Michael Steiner et al.

Michael Steiner et al.


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Short summary
The Paris Agreement increased the interest in estimating GHG emissions of individual countries, but top-down emission estimation is not yet considered policy-relevant. It is therefore paramount to reduce the large errors and to build systems that are based on the newest atmospheric transport models (e.g., ICON-ART). In this study, we present the first application of ICON-ART in inverse modelling of GHG fluxes with an Ensemble Kalman Filter and present our results for European CH4 emissions.