Exploring the mitigation potential role of legumes in European agriculture – a modelling approach
Item statusRestricted Access
Embargo end date31/12/2100
Angelopoulos, Nikolaos G.
The increasing atmospheric concentration of greenhouse gases (GHG) has direct consequences on humans and threatens the sustainability of natural and managed ecosystems. The European Union has set high targets for reducing their emissions by 80‐95% of the 1990 levels by 2050 and is working progressively to achieve these reductions. Legumes are an important group of crop species as they have the potential to reduce N2O emissions. Biogeochemical modelling can provide a valuable tool to explore options for mitigating GHG emissions and especially N2O from European agriculture by simulating novel legume based rotations. UK‐DNDC is a process based, biogeochemical model that can be used towards that goal. The model was tested for various regions in Europe and showed that it can simulate the N dynamics within crop rotations across a range of pedoclimatic zones. It is a useful tool in 1) identifying where and when high emissions occur, 2) highlighting the effects of the management practices on emissions and 3) exploring the impact of alternative managements on emissions. New rotations, which include legumes, have been proposed in order to assess the sustainability of the legumes in European agriculture and the effect that they will have on N2O production. Five regions in Europe, namely Sweden, Germany, Italy, Scotland and Romania, were selected in order to test the differences between legume based rotations and non‐legume based. These regions represent a wide range of pedo‐climatic zones in Europe. In most case studies, legumes showed that they can make an important contribution to mitigating N2O emissions. However, there were cases in which legumes enhanced the production of N2O. Modelling can help to understand system dynamics and it can also help to explore mitigation options for European agriculture in terms of N2O production. An important element of environmental modelling is to understand the uncertainty and sensitivity of model parameters in relation to the model outputs. The sensitivity testing of the model showed that clay content, initial soil organic carbon content and atmospheric background CO2 concentration are three key input parameters Nitrous oxide emissions were one of the results that showed great uncertainty in all the analyses. That highlights the challenges of the modelling activity for accurate N2O simulations in a dynamic ecosystem.