Process-based model estimation of N2O Emission factors for urine patches in a Swiss grazing system
- 1Climate and Agriculture group-Agroscope, Reckenholzstrasse 191, 8046 Zürich
- 2ETH Zürich, Institute of Agricultural Sciences (IAS) – Sustainable Agroecosystems, Tannenstrasse 1, 8092 Zürich
Nitrous oxide (N2O) is a powerful greenhouse gas (GHG) with a global warming potential about 300 times that of carbon dioxide (CO2). In Switzerland, N2O emissions contribute to about 6% of the total GHG emissions, agriculture being responsible for more than 60% of the former. Understanding the processes driving N2O emissions from agricultural land is therefore of paramount importance for developing national GHG emissions inventories. Of relevance in this respect is the fact that about two-thirds of the agricultural lands are grasslands, part of which are managed as pastures.
Urine deposited by grazing animals has high N loads and induce increased nitrification and denitrification. Urine patches are hence hotspots for N2O emissions. In the IPCC Tier 1 method still in use in Switzerland for quantifying N2O emissions, a default EF3 value of 2% is assumed for excreta (dung and urine). This does not properly account for the spatial heterogeneity of N returns from grazing animals. Recent studies have indeed shown that country-specific EF3 are typically much lower than the default IPCC value. These results suggest that the use of IPCC Tier 2 and Tier 3 methods, that rely on the application of process-based models, is to be preferred for estimating countrywide N2O emissions.
In this work, we will apply the comprehensive process-based model ecosys to simulate N2O emissions from urine patches in a Swiss grazing system. We report on preliminary results from experiments aiming at modelling artificially applied urine patches. After showing that the model is able to reproduce the emission rates measured in a companion field trial, we use ecosys to examine N fractions lost to direct (N2O emissions) and indirect (ammonia volatilization, nitrate leaching and runoff) pathways for urine-N input rates varying from 500-2000 kg N ha-1. We also apply the model to understand the effects of seasonal variations in the environmental drivers on N2O EF. This work is part of a PhD conducted by the first author that aims at developing the scientific basis for establishing country-specific EFs for grazing-related N2O emissions in Switzerland.
How to cite: Kuntu-Blankson, K., Six, J., Barczyk, L., Ammann, C., and Calanca, P.: Process-based model estimation of N2O Emission factors for urine patches in a Swiss grazing system , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13220, https://doi.org/10.5194/egusphere-egu21-13220, 2021.