Robust models for assessing the effectiveness of technologies and managements to reduce N2O emissions from grazed pastures (Models4Pastures)

Agricultural cultivation systems such as grazed pastures are characterized by considerable nitrogen losses in the form of the greenhouse gas nitrous oxide. This project seeks possible ways to improve currently available models to estimate nitrous oxide emissions from grazed pastures.

The Models4Pastures project is funded under the Joint Programming Initiative on Agriculture, Food Security and Climate Change (FACCE-JPI). It is a collaboration between New Zealand, the UK, Italy, Switzerland and France


Little is known about the spatial and temporal differences between pasture systems in nitrous oxide emissions. Continuous and high resolution time measurements of N2O exchange are difficult to make; current model estimates are extremely inaccurate. The modelling of livestock grazing systems is also made more difficult by the animals’ selective grazing and the associated displacement of system nutrients to relatively small patches of dung and urine. Various simulation models are available for grazed pasture systems but only a few studies have compared the models. Comparisons are essential so that we can improve the tools for assessing potential mitigation options of nitrous oxide emissions.

The Project

Models4Pastures aims to improve the currently available models. The researchers will not only compare the performance of different models but also quantify the nitrous oxide emissions of individual grazing areas. In addition, they will test how useful the different models are to describe a recently collected dataset of continuous, high resolution time measurements of nitrous oxide gas exchange of pasture land in Switzerland. The newly gained knowledge will be implemented in the existing models, which will improve the prediction of nitrous oxide emissions of pastures. In a final step, the improved models will be used for evaluation of various emission reduction scenarios.

Dr. Lutz Merbold

ETH Zürich

Project leader

Val Snow

Project Coordinator