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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 6 | Copyright
Atmos. Chem. Phys., 16, 3683-3710, 2016
https://doi.org/10.5194/acp-16-3683-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 21 Mar 2016

Research article | 21 Mar 2016

Validation of the Swiss methane emission inventory by atmospheric observations and inverse modelling

Stephan Henne1, Dominik Brunner1, Brian Oney1, Markus Leuenberger2, Werner Eugster3, Ines Bamberger3,4, Frank Meinhardt5, Martin Steinbacher1, and Lukas Emmenegger1 Stephan Henne et al.
  • 1Empa Swiss Federal Laboratories for Materials Science and Technology, Überlandstrasse 129, Dübendorf, Switzerland
  • 2Univ. of Bern, Physics Inst., Climate and Environmental Division, and Oeschger Centre for Climate Change Research, Bern, Switzerland
  • 3ETH Zurich, Inst. of Agricultural Sciences, Zurich, Switzerland
  • 4Institute of Meteorology and Climate Research Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany
  • 5Umweltbundesamt (UBA), Kirchzarten, Germany

Abstract. Atmospheric inverse modelling has the potential to provide observation-based estimates of greenhouse gas emissions at the country scale, thereby allowing for an independent validation of national emission inventories. Here, we present a regional-scale inverse modelling study to quantify the emissions of methane (CH4) from Switzerland, making use of the newly established CarboCount-CH measurement network and a high-resolution Lagrangian transport model. In our reference inversion, prior emissions were taken from the "bottom-up" Swiss Greenhouse Gas Inventory (SGHGI) as published by the Swiss Federal Office for the Environment in 2014 for the year 2012. Overall we estimate national CH4 emissions to be 196 ± 18 Gg yr−1 for the year 2013 (1σ uncertainty). This result is in close agreement with the recently revised SGHGI estimate of 206 ± 33 Gg yr−1 as reported in 2015 for the year 2012. Results from sensitivity inversions using alternative prior emissions, uncertainty covariance settings, large-scale background mole fractions, two different inverse algorithms (Bayesian and extended Kalman filter), and two different transport models confirm the robustness and independent character of our estimate. According to the latest SGHGI estimate the main CH4 source categories in Switzerland are agriculture (78 %), waste handling (15 %) and natural gas distribution and combustion (6 %). The spatial distribution and seasonal variability of our posterior emissions suggest an overestimation of agricultural CH4 emissions by 10 to 20 % in the most recent SGHGI, which is likely due to an overestimation of emissions from manure handling. Urban areas do not appear as emission hotspots in our posterior results, suggesting that leakages from natural gas distribution are only a minor source of CH4 in Switzerland. This is consistent with rather low emissions of 8.4 Gg yr−1 reported by the SGHGI but inconsistent with the much higher value of 32 Gg yr−1 implied by the EDGARv4.2 inventory for this sector. Increased CH4 emissions (up to 30 % compared to the prior) were deduced for the north-eastern parts of Switzerland. This feature was common to most sensitivity inversions, which is a strong indicator that it is a real feature and not an artefact of the transport model and the inversion system. However, it was not possible to assign an unambiguous source process to the region. The observations of the CarboCount-CH network provided invaluable and independent information for the validation of the national bottom-up inventory. Similar systems need to be sustained to provide independent monitoring of future climate agreements.

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Greenhouse gas emissions can be assessed by "top-down" methods that combine atmospheric observations, a transport model and a mathematical optimisation framework. Here, we apply such a top-down method to the methane emissions of Switzerland, utilising observations from the recently installed CarboCount-CH network. Our Swiss total emissions largely agree with those of the national "bottom-up" inventory, whereas regional differences suggest lower than reported emissions from manure handling.
Greenhouse gas emissions can be assessed by "top-down" methods that combine atmospheric...
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