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

Abstract

Abstract. We present the first high-resolution (500 m × 500 m) gridded methane (CH 4 ) emission inventory for Switzerland, which integrates 90 % of the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH 4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH 4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH 4 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 CH 4 emissions in 2011 originated from the agricultural sector (150 Gg CH 4 yr −1 ), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH 4 yr −1 ) mainly from landfills and the energy sector (12 Gg CH 4 yr −1 ), which was dominated by emissions from natural gas distribution. Compared with the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH 4 yr −1 ), making up only 3 % of the total emissions in Switzerland. CH 4 fluxes from agricultural soils were estimated to be not significantly different from zero (between −1.5 and 0 Gg CH 4 yr −1 ), while forest soils are a CH 4 sink (approx. −2.8 Gg CH 4 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 an European (TNO/MACC) CH 4 inventory. This new spatially explicit emission inventory for Switzerland will provide valuable input for regional-scale atmospheric modeling and inverse source estimation.

Continuous CO<sub>2</sub>/CH<sub>4</sub>/CO measurements (2012–2014) at Beromünster tall tower station in Switzerland

“…The wider scatter (r 2 = 0.54 for January) and the lower ratio of the emissions at the lowest level suggest larger than average local emissions of CH 4 . This is in agreement with the location of the tower in an area dominated by agricultural use (Hiller et al, 2014).…”

“…The seasonality in the observation-based ratios is likely dominated by the seasonality in CO emissions, which are expected to peak during the cold season. Anthropogenic sources of CH 4 , conversely, are expected to be relatively constant over the year (Hiller et al, 2014), though there is a tendency to smaller emissions in the cold season (Henne et al, 2016).…”

Eddy covariance methane flux measurements over a grazed pasture: effect of cows as moving point sources

“…Agriculture is estimated to contribute about 50 % of total anthropogenic emissions of CH 4 , while enteric fermentation of livestock alone accounts for about one-third (Smith et al, 2007). For Switzerland these numbers are even higher, with 85 %total agricultural contribution and 67 % from enteric fermentation alone, although still afflicted with considerable uncertainty (Hiller et al, 2014). Measurements of these emissions are therefore important for national GHG inventories and for assessing their effect on the global scale.…”

Validation of farm-scale methane emissions using nocturnal boundary layer budgets

“…NIR and SEI), which both use the same estimation methodology, but differ in their spatial resolution. While the NIR evaluated CH 4 emissions on an annual basis for entire Switzerland (FOEN, 2015), the recently developed SEI (Hiller et al, 2014a) distributed the CH 4 emissions, based on the 2007 year stocking census data (FSO, 2009), onto a 500 m × 500 m grid according to Swiss land use statistics (FSO, 2007) and then scaled the emissions to represent 2011 livestock numbers (see Hiller et al, 2014a). Both inventories estimate the CH 4 emissions from national livestock numbers multiplied with animal-specific emission factors, i.e.…”

“…In the SEI, the Chamau research station was explicitly resolved by several grid cells, with CH 4 emissions ranging from 6 to 820 kg CH 4 ha −1 yr −1 . This large variation among the individual grid cells arises due to the standardized assignment process of the SEI: about 80 % of the CH 4 emissions are assigned to the grid cell with the main building of a farmstead, while the remaining emissions are evenly distributed to the pasture area of the entire municipality (Hiller et al, 2014a).…”