Nitrous oxide (N₂O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N₂O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N₂O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N₂O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N₂O emissions are reviewed regarding their ability to consider the impact factors in simulating N₂O. The model strengths and weaknesses in simulating N₂O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N₂O emissions from cropping systems. Their ability to simulate N₂O emissions is evaluated by describing the model components that are relevant to N₂O processes and their representation in the model.

Nitrous oxide (N₂O) is a potent greenhouse gas stemming mainly from nitrogen (N)-fertilizer application. It is challenging to quantify N₂O emissions from agroecosystems because of the dearth of measured data and high spatial variability of the emissions. The eco-hydrological model SWAT (Soil and Water Assessment Tool) simulates hydrological processes and N fluxes in a catchment. However, the routine for simulating N₂O emissions is still missing in the SWAT model. A submodule was developed based on the outputs of the SWAT model to partition N₂O from the simulated nitrification by applying a coefficient (K₂) and also to isolate N₂O from the simulated denitrification (N₂O + N₂) with a modified semi-empirical equation. The submodule was applied to quantify N₂O emissions and N₂O emission factors from selected crops in two agricultural catchments by using NH₄NO₃ fertilizer and the combination of organic N and NO₃⁻ fertilizer as N input data. The setup with the combination of organic N and NO₃⁻ fertilizer simulated lower N₂O emissions than the setup with NH₄NO₃ fertilizer. When the water balance was simulated well (absolute percentage error <11%), the impact of N fertilizer application on the simulated N₂O emissions was captured. More research to test the submodule with measured data is needed.