EGU24-11377, updated on 09 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Pasture N2O emission fluxes by eddy covariance - partitioning and driver analysis

Christof Ammann and Lena Barczyk
Christof Ammann and Lena Barczyk
  • Agroscope Research Institute, Climate and Agriculture Group, Zuerich, Switzerland (

Grazed and fertilized pastures are considerable sources of the greenhouse gas N2O. While fertilizer applications usually lead to short emission pulses, animal excreta lead to small-scaled emission hotspots resulting in a non-homogeneous source distribution. The strong spatial and temporal source variability represents an inherent problem for the quantification of gaseous emissions from pastures with chamber techniques. The eddy covariance method, integrating emissions over a larger footprint domain, is well suited to quantify total field-scale N2O emissions, but the partitioning of emissions for different sources and the determination of source-specific emission factors (according to the IPCC guidelines) is still a challenge.

We present results of two multiple-year field experiments carried out in different regions of Switzerland. The investigated pastures were grazed by dairy cows in an intensive rotational management. The fields were additionally fertilized with organic and/or mineral fertilizer. The field-scale N2O fluxes were quantified with the eddy covariance technique using a fast response Quantum cascade laser spectrometer for N2O concentration measurements. The management and environmental conditions resulted in high temporal and spatial dynamics of the N2O fluxes with highest values typically occurring after fertilization events in the summer months. Total annual N2O emissions amounted to between 2.5 and 5 kg N ha-1 y-1. Data-based partitioning methods of different complexity were used to attribute the observed field-scale emissions to the main source classes (grazing excreta, fertilizer application, and background) and to derive annual N2O emission factors. Using random forest and other regression methods the effect of environmental parameters on grazing-related emissions were analyzed.

How to cite: Ammann, C. and Barczyk, L.: Pasture N2O emission fluxes by eddy covariance - partitioning and driver analysis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11377,, 2024.