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| Titel |
Spatially explicit methane inventory for Switzerland |
| VerfasserIn |
Rebecca Hiller, Daniel Bretscher, Tonya DelSontro, Werner Eugster, Stephan Henne, Ruth Henneberger, Thomas Künzle, Lutz Merbold, Bruno Neininger, Andreas Schellenberger, Martin Schroth, Nina Buchmann, Dominik Brunner |
| Konferenz |
EGU General Assembly 2013
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| Medientyp |
Artikel
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| Sprache |
Englisch
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 15 (2013) |
| Datensatznummer |
250083044
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| Zusammenfassung |
| Spatially explicit greenhouse gas inventories are gaining in importance as a tool for policy
makers to plan and control mitigation measures, and are a required input for atmospheric
models used to relate atmospheric concentration measurements with upstream sources. In
order to represent the high spatial heterogeneity in Switzerland, we compiled the national
methane inventory into a 500 m x 500Â m cadaster. In addition to the anthropogenic emissions
reported to the United Nation Framework Convention on Climate Change (UNFCCC), we
also included natural and semi-natural methane fluxes, i.e., emissions from lakes and
reservoirs, wetlands, wild animals as well as forest uptake. Methane emissions were
disaggregated according to geostatistical information about source location and
extent. In Switzerland, highest methane emissions originate from the agricultural
sector (152 Gg CH4 yr-1), followed by emissions from waste management (16 Gg
CH4 yr-1) with highest contributions from landfills, and the energy sector (13 Gg
CH4 yr-1) with highest contributions from the distribution of natural gas. Natural
and semi-natural emissions only add a small amount (< 5%) to the total Swiss
emissions.
For validation, the bottom-up inventory was evaluated against methane concentrations
measured from a small research aircraft (METAIR-DIMO) above the Swiss Plateau
on 18 different days from May 2009 to August 2010 over. Source sensitivities of
the air measured were determined by backward runs of the Lagrangian particle
dispersion model FLEXPART-COSMO. Source sensitivities were multiplied with the
methane inventory to derive simulated methane concentration time series. While the
pattern of the variations can be reproduced well for some flight days (correlation
coefficient up to 0.75), the amplitude of the variations for the simulated time series is
underestimated by at least 20% suggesting an underestimation of CH4 emissions by the
inventory, which is also concluded from inverse estimation using a Bayesian approach. |
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