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| Titel |
Estimation of Swiss methane emissions by near surface observations and inverse modeling |
| VerfasserIn |
Stephan Henne, Brian Oney, Markus Leuenberger, Ines Bamberger, Werner Eugster, Martin Steinbacher, Frank Meinhardt, Dominik Brunner |
| Konferenz |
EGU General Assembly 2015
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 17 (2015) |
| Datensatznummer |
250112904
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| Publikation (Nr.) |
 EGU/EGU2015-13091.pdf |
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| Zusammenfassung |
| On a global scale methane (CH4) is the second most important long-lived greenhouse gas. It
is released from both natural and anthropogenic processes and its atmospheric burden has
more than doubled since preindustrial times. Current CH4 emission estimates are associated
with comparatively large uncertainties both globally and regionally. For example, the Swiss
national greenhouse gas inventory assigns an uncertainty of 18% to the country total
anthropogenic CH4 emissions as compared to only 3% for anthropogenic CO2 emissions. In
Switzerland, CH4 is thought to be mainly released by agricultural activities (ruminants
and manure management >80%), while natural emissions from wetlands and wild
animals represent a minor source (~3 %). The country total and especially the spatial
distribution of CH4 emission within Switzerland strongly differs between the national and
different European scale inventories. To validate the “bottom-up” Swiss CH4 emission
estimate and to reduce its uncertainty both in total and spatially, “top-down” methods
combining atmospheric CH4 observations and regional scale transport simulations can be
used.
Here, we analyse continuous, near surface observations of CH4 concentrations
as collected within the newly established CarboCountCH measurement network
(http://www.carbocount.ch). The network consists of 4 sites situated on the Swiss Plateau,
comprising a tall tower site (217 m), two elevated (mountaintop) sites and a small tower site
(32 m) in flat terrain. In addition, continuous CH4 observations from the nearby high-altitude
site Jungfraujoch (Alps) and the mountaintop site Schauinsland (Germany) were used. Two
inversion frameworks were applied to the CH4 observations in combination with
source sensitivities (footprints) calculated with the regional scale version of the
Lagrangian Particle Dispersion Model FLEXPART. One inversion system was based on a
Bayesian framework, while the other utilized an extended Kalman filter approach. The
transport model was driven by analysis fields from the non-hydrostatic numerical
weather predication model COSMO at horizontal resolutions of up to 7 km x 7
km. As a result spatially resolved, annual mean CH4 fluxes for Switzerland were
obtained. In general total Swiss CH4 emission remained close to the “bottom-up”
estimates, while considerable shifts in the regional distribution of the emissions
were obtained. Reductions in CH4 emissions, as compared to the prior estimates,
were established in regions with large emissions from ruminants, while increases
resulted in the Western part of the Swiss Plateau, which is dominated by mixture of
large water bodies and crop and vegetable farming. Sensitivity inversions were
applied to assess the overall robustness and the uncertainty of the inversion system. |
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