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.
The performance of Oniscus asellus (Isopoda) and its influence on litter mass loss and mineralization was assessed in a microcosm experiment, using beech (Fagus sylvatica) leaf litter that was produced on different soil types, contrasting atmospheric CO2 concentrations, and different nitrogen deposition rates. Litter quality was significantly altered by these treatments, and many of the CO2 and N effects differed between soil types. Litter quality affected subsequent litter mass loss rates, microbial respiration, and leaching of dissolved organic carbon (DOC) and nitrate. These effects were largely independent of the presence of isopods, even though isopods highly accelerated litter mass loss, stimulated microbial respiration by 37%, and increased nitrate leaching by 50%. Isopods did not change their relative rates of litter consumption and growth in response to litter quality. Isopod mortality, however, increased with increasing litter lignin/N ratios, and was significantly different between soil types, which may indicate long‐term effects on litter decomposition through altered isopod densities. Having the choice among the litter of three different species [maple (Acer pseudoplatanus), beech (Fagus sylvatica) and oak (Quercus robur)] grown at either ambient or elevated CO2, isopods preferred maple to beech when all the litter was produced under elevated CO2. This suggests that beyond changes in consumption, an altered food selection by isopods in a CO2‐enriched atmosphere may affect the temporal and spatial composition of the litter layer in temperate forests. In contrast to previous findings, we conclude that isopods do not always increase their consumption rates, and hence do not differentially affect microbial decomposition in litter of poorer quality. Nevertheless changes in animal densities and/or shifts in their food preferences, could result in altered decomposition and carbon and nutrient turnover rates.
For regional‐scale investigations of greenhouse gas budgets the spatially explicit information from local emission sources is needed, which then can be compared with flux measurements. Here we present the first validation of a section of a spatially explicit CH4 emission inventory of Switzerland. The validation was done for the agriculturally dominated Reuss Valley using measurements from a low‐flying aircraft (50–500 m above ground level). We distributed national emission estimates to a grid with 500 m cell size using available geostatistical data. Validation flux measurements were obtained using the eddy covariance (EC) technique and the boundary layer budgeting (BLB) approach that only uses the mean concentrations of the same aircraft transects. Inventory estimates for the flux footprint of the aircraft measurements were lowest (median 0.40 μg CH4m−2s−1), and BLB fluxes were highest (1.02 μg CH4m−2s−1) for the Reuss Valley, with EC fluxes in between (0.62 μg CH4m−2s−1). Flux estimates from measurements and inventory are within the same order of magnitude, but measured fluxes were significantly larger than the inventory emission estimates. The differences are larger than the uncertainties associated with storage of manure, temperature dependence of emissions, diurnal cycle of enteric fermentation by cattle, and the limitations of the inventory that only covers ≥90% of all expected methane emissions. From this we deduce that it is not unlikely that the Swiss CH4 emission inventory estimates are too low.
Abstract. Carbon (C) sequestration in the soil is considered as a potential important mechanism to mitigate greenhouse gas (GHG) emissions of the agricultural sector. It can be quantified by the net ecosystem carbon budget (NECB) describing the change of soil C as the sum of all relevant import and export fluxes. NECB was investigated here in detail for an intensively grazed dairy pasture in Switzerland. Two budget approaches with different system boundaries were applied: NECB tot for system boundaries including the grazing cows and NECB past for system boundaries excluding the cows. CO 2 and CH 4 exchange induced by soil/vegetation processes as well as direct emissions by the animals were derived from eddy covariance measurements. Other C fluxes were either measured (milk yield, concentrate feeding) or derived based on animal performance data (intake, excreta). For the investigated year, both approaches resulted in a small near-neutral C budget: NECB tot −27 ± 62 and NECB past 23 ± 76 g C m −2 yr −1 . The considerable uncertainties, depending on the approach, were mainly due to errors in the CO 2 exchange or in the animal-related fluxes. The comparison of the NECB results with the annual exchange of other GHG revealed CH 4 emissions from the cows to be the major contributor in terms of CO 2 equivalents, but with much lower uncertainty compared to NECB. Although only 1 year of data limit the representativeness of the carbon budget results, they demonstrate the important contribution of the non-CO 2 fluxes depending on the chosen system boundaries and the effect of their propagated uncertainty in an exemplary way. The simultaneous application and comparison of both NECB approaches provides a useful consistency check for the carbon budget determination and can help to identify and eliminate systematic errors.
Process-based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N 2 O) fluxes remain challenging. Models are limited by our understanding of soil-plant-microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N 2 O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N 2 O fluxes on annual timescales, while APSIM was most accurate for daily N 2 O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)-derived method for the Swiss agricultural GHG inventory (IPCC-Swiss), but individual models were not systematically more accurate than IPCC-Swiss. The model ensemble overestimated the N 2 O mitigation effect of the clover-based treatment (measured: 39-45%; ensemble: 52-57%) but was more accurate than IPCC-Swiss (IPCC-Swiss: 72-81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N 2 O emissions. Plain Language SummaryWe tested the performance of three dynamic simulation models against measured nitrous oxide (N 2 O) fluxes and its driver variables for a Swiss grassland. We showed that DayCent performed best in the prediction of annual N 2 O emissions but was outperformed by APSIM for daily N 2 O emissions. We identified particular strengths and weaknesses of each model. Further, we compared the individual models against the N 2 O flux estimate made with the Intergovernmental Panel on Climate Change (IPCC)-derived method for the Swiss agricultural greenhouse gas inventory (IPCC-Swiss). Most individual models were worse than IPCC-Swiss but the mean of all model predictions was much better than IPCC-Swiss. All methods overestimated the N 2 O mitigation effect of a clover-based N 2 O mitigation. IPCC-Swiss was worst and the model ensemble was best at estimating the effects of the mitigation. The findings highlight that using multiple models in an ensemble is beneficial for assessing management and climate impacts on N 2 O emissions.
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