Inverse modelling of European CH4 emissions during 2006–2012 using different inverse models and reassessed atmospheric observations
Peter Bergamaschi1, Ute Karstens2,3, Alistair J. Manning4, Marielle Saunois5, Aki Tsuruta6, Antoine Berchet5,7, Alexander T. Vermeulen3,8, Tim Arnold4,9,10, Greet Janssens-Maenhout1, Samuel Hammer11, Ingeborg Levin11, Martina Schmidt 11, Michel Ramonet5, Morgan Lopez5, Jost Lavric2, Tuula Aalto6, Huilin Chen12,13, Dietrich G. Feist2, Christoph Gerbig2, László Haszpra14,15, Ove Hermansen16, Giovanni Manca1, John Moncrieff10, Frank Meinhardt17, Jaroslaw Necki18, Michal Galkowski18, Simon O'Doherty19, Nina Paramonova20, Hubertus A. Scheeren12, Martin Steinbacher7, and Ed Dlugokencky211European Commission Joint Research Centre, Ispra (Va), Italy 2Max Planck Institute for Biogeochemistry, Jena, Germany 3ICOS Carbon Portal, ICOS ERIC, University of Lund, Sweden 4Met Office Exeter, Devon, UK 5Laboratoire des Sciences du Climat et de l’Environnement (LSCE-IPSL), CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France 6Finnish Meteorological Institute (FMI), Helsinki, Finland 7Swiss Federal Laboratories for Materials Science and Technology (Empa), Dübendorf, Switzerland 8Energy research Centre of the Netherlands (ECN), Petten, the Netherlands 9National Physical Laboratory, Teddington, Middlesex, TW11 0LW, UK 10School of GeoSciences, The University of Edinburgh, Edinburgh, EH9 3FF, UK 11Institut für Umweltphysik, Heidelberg University, Germany 12Center for Isotope Research (CIO), University of Groningen, the Netherlands 13Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, CO, USA 14Hungarian Meteorological Service, Budapest, Hungary 15Research Centre for Astronomy and Earth Sciences, Geodetic and Geophysical Institute, Sopron, Hungary 16Norwegian Institute for Air Research (NILU), Norway 17Umweltbundesamt, Messstelle Schauinsland, Kirchzarten, Germany 18AGH University of Science and Technology, Krakow, Poland 19Atmospheric Chemistry Research Group, University of Bristol, Bristol, UK 20Voeikov Main Geophysical Observatory, St. Petersburg, Russia 21NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, CO, USA
Received: 23 Mar 2017 – Accepted for review: 29 Mar 2017 – Discussion started: 07 Apr 2017
Abstract. We present inverse modelling (top-down) estimates of European methane (CH4) emissions for 2006–2012 based on a new quality-controlled and harmonized in-situ data set from 18 European atmospheric monitoring stations. We applied an ensemble of seven inverse models and performed four inversion experiments, investigating the impact of different sets of stations and the use of a priori information on emissions.
The inverse models infer total CH4 emissions of 26.7 (20.2–29.7) Tg CH4 yr−1 (mean, 10th and 90th percentiles from all inversions) for the EU-28 for 2006–2012 from the four inversion experiments. For comparison, total anthropogenic CH4 emissions reported to UNFCCC (bottom-up, based on statistical data and emissions factors) amount to only 21.3 Tg CH4 yr−1 (2006) to 18.8 Tg CH4 yr−1 (2012). A potential explanation for the higher range of top-down estimates compared to bottom-up inventories could be the contribution from natural sources, such as peatlands, wetlands, and wet soils. Based on seven different wetland inventories from the Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) total wetland emissions of 4.3 (2.3–8.2) CH4 yr−1 from EU-28 are estimated. The hypothesis of significant natural emissions is supported by the finding that several inverse models yield significant seasonal cycles of derived CH4 emissions with maxima in summer, while anthropogenic CH4 emissions are assumed to have much lower seasonal variability.
Furthermore, we investigate potential biases in the inverse models by comparison with regular aircraft profiles at four European sites and with vertical profiles obtained during the Infrastructure for Measurement of the European Carbon Cycle (IMECC) aircraft campaign. We present a novel approach to estimate the biases in the derived emissions, based on the comparison of simulated and measured enhancements of CH4 compared to the background, integrated over the entire boundary layer and over the lower troposphere. This analysis identifies regional biases for several models at the aircraft profile sites in France, Hungary and Poland.
Bergamaschi, P., Karstens, U., Manning, A. J., Saunois, M., Tsuruta, A., Berchet, A., Vermeulen, A. T., Arnold, T., Janssens-Maenhout, G., Hammer, S., Levin, I., Schmidt , M., Ramonet, M., Lopez, M., Lavric, J., Aalto, T., Chen, H., Feist, D. G., Gerbig, C., Haszpra, L., Hermansen, O., Manca, G., Moncrieff, J., Meinhardt, F., Necki, J., Galkowski, M., O'Doherty, S., Paramonova, N., Scheeren, H. A., Steinbacher, M., and Dlugokencky, E.: Inverse modelling of European CH4 emissions during 2006–2012 using different inverse models and reassessed atmospheric observations, Atmos. Chem. Phys. Discuss., doi:10.5194/acp-2017-273, in review, 2017.