Anthropogenic and natural methane fluxes in Switzerland synthesized within a spatially-explicit inventory

R. V. Hiller, D. Bretscher, T. DelSontro, T. Diem, W. Eugster, R. Henneberger, S. Hobi, E. Hodson, D. Imer, M. Kreuzer, T. Künzle, L. Merbold (+9 others)
2013 Biogeosciences Discussions  
We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest
more » ... as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process-or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4 yr−1), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4 yr−1) mainly from landfills and the energy sector (12 Gg CH4 yr−1), which was dominated by emissions from natural gas distribution. Compared to the anthropogenic sources, emissions from natural and seminatural sources were relatively small (6 Gg CH4 yr−1), making up only 3 % of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between −1.5 and 0 Gg CH4 yr−1), while forest soils are a CH4 sink (approx. −2.8 Gg CH4 yr−1), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and a European CH4 inventory (TNO/MACC). This new spatially-explicit emission inventory for Switzerland will provide valuable input for regional scale atmospheric modeling and inverse source estimation.
doi:10.5194/bgd-10-15181-2013 fatcat:psjw3qyx6nfntmx7o5gudi2q4y