N2O emission in soils is a consequence of the activity of nitrifying and denitrifying microorganisms and potentially abiotic processes. However, the large microscale variability of the soil characteristics that influence these processes and in particular the location of anoxic microsites, limits prediction efforts. Better understanding of denitrification activity on microscopic scales is required to improve predictions of N2O emissions. This study explored the role of soil microstructure on N2O emission. To fulfill this objective we sampled 24 soil columns (5 cm diameter, 6 cm height) in the surface layer of a same plot in a cultivated soil (Luvisol, La Cage, Versailles, France). The soil samples were saturated with a solution of ammonium nitrate (NH4NO3), and equilibrated at a matrix potential of -32 cm (pF 1.5). The emitted fluxes of N2O were measured during 7 days. At the end of the experiment, the soil columns were scanned in a X-ray micro tomograph, at the University of Poitiers. A 32 µm voxel resolution was achieved for the 3D reconstructed images. In order to reduce noise and segment the 3D images, the same protocol was implemented for all columns. The reduction of noise consisted of passing a non-local mean filter, a non-sharp mask and a radial correction. Such combination of steps succeeded in removing both ring artifacts and the radial dependence of the voxel values. Due to the variety of material densities in the soil, a local segmentation based on the watershed method was implemented to classify the soil constituents in four classes (based on its density value): air, water and organic matter (OM), soil matrix and minerals. This method is good for detecting thin pores and avoids missclassification of voxels undergoing partial volume effect, which can lead to false organic coatings around macropores. The soil columns exhibited a large variability of accumulated N2O after 7 days (from 107 to 1940 µgN kg-1 d.w. soil). The size of OM clusters varied between a couple and up to thousands of voxels. No correlation was found between the emission of N2O and the porosity, nor between the N2O emission and the connectivity of the air phase. Based on the premise that the less accessible is the oxygen to the OM, the bigger should be the N2O emission of the soil column, we proposed and computed a microscopic spatial descriptor, Igd, based on the notion of the geodesic distance between clusters of OM and air for each soil column 3D image. We expect to find a correlation between Igd and the N2O emission.