Soil aggregates are considered as an important indicator, reflecting many basic soil characteristics including organic matter composition and the pattern of its microbial transformation. Different type of agricultural practices as well as the processes of wind and water erosions affect the soil aggregate structure leading degradation of specific soil organic compounds – Humic Substances (HS). HS is a natural organic polymers which is very resistant for microbial transformation. The period of HS degradation takes a few thousand years and deposit amount of carbon in soil estimated as 70-120 T/ha. The limited number predominantly aerobic microorganisms involved in the process of HS transformation determine high resistance potential of HS in soil especially in anaerobic micro-sites usually formed inside of soil aggregates. The present research aimed to study the rate of HS microbial transformation in soil aggregates (carbon dioxide, methane and nitrous oxide production) and choose important parameters in soil structure for simulation model of carbon stock in soil modul of C-cycle. In our report we discuss peculiarities of microbial distribution inside and on the surface of soil aggregates; the process of anaerobic zones formation within the soil aggregates; the role of molecular hydrogen in organic matter transformation within the soil aggregates; microbial communities in soil aggregates; resistance for the negative anthropogenic impacts, to human intervention and management; exchange rate of greenhouse gases (CO2, CH4 and N2O) between soils and the atmosphere. Obtained results showed accumulation of organic matter in the soil aggregates of a large sizes (2-3 mm in diameter) with a growth rate of hydrophobic fractions in HS from such aggregates dimension. It may be explained as specific pathway of organic matter transformation in anaerobic micro-zones inside of soil aggregates. We can conclude that soil structure is an important parameter that should be taking into account by a carbon cycle model for providing quantifiable predictions of carbon stock changes specially under anthropogenic influence.