The reduction of greenhouse gas emissions by improving the efficiency of agricultural systems through robust ecologically-based management practices represents the most important challenge facing agriculture. Models are needed to evaluate the effects of soil properties, climate, and agricultural management practices on soil carbon and on the nitrogen transformations responsible for GHG emissions. Models of Carbon and nitrogen cycles in soils need improvements so they can provide more accurate and robust predictions. They use empirical functions which account for the different environmental factors that affect microbial functions. However, these types of function have limitations because they don’t consider the micro heterogeneity of soil at the scale of microorganisms and they cannot describe processes that are connected to each other by complex interactions linked to soil structure. Mechanistic representation of small-scale processes was identified in literature as one of the priorities to improve these global soil organic matter dynamics models. Our previous project showed the importance of the habitat of soil microorganisms, and especially how physical characteristics (pore sizes, connectivity) control the decomposition of organic substrates via experimental microcosm. We have developed a suite of methods and models to visualize in 2D or 3D soil heterogeneity at scales relevant for microorganisms. It has also contributed to the development of three very complementary 3D models able to simulate for the first time the microbial degradation of organic matter at the scale of microhabitats in soil using real 3D images of soils. The goal of this Soilµ3D project is now to go further by using the 3D models resulting from MEPSOM to upscale heterogeneities identified at the scale of microhabitats to the soil profile scale. The aims of the project are to: develop new descriptors of the pore scale 3D soil heterogeneity that explain the fluxes measured at the core scale, use our 3D models to connect the µ-scale heterogeneity and the measured macroscale fluxes, develop new simple models describing the soil micro-heterogeneity and integrating these micro-features into field-scale models. Several improvements have been made to 3D models, such as: i) model parallelization, ii) more compact representation of pore space by ellipsoids as geometric primitives, iii) coupling with Individual based models. Two Literature reviews were written concerning technics of 3D images at small scale (Baveye et al, 2018) and the 3D modelling of soil pores microscopic architecture (Pot et al., 2020) . Modeling scenarios from 3D soil images has shown the importance of the connectivity of water-filled pores in carbon mineralization. The number of clusters of pores filled with water appears to be a relevant indicator of CO2 emissions. This modeling shows that the diffusion of the 3D substrate controls the contact between µorganisms and organic matter and therefore the rates of decomposition. A threshold effect is observed with an increase in the decomposition of organic matter when low substrate concentrations are associated with a high number of bacterial cells compared to a population model.