CO2 corrosion is a serious environmental and financial concern for the oil and gas industry requiring the continuous development of cost-effective corrosion prevention and mitigation strategies. Over the last decades, the FeCO3 scale that forms during the CO2 corrosion process has gained much interest as it can prevent further corrosion once fully formed. However, fundamental research on CO2 corrosion and the formation of these corrosion scales is still lacking due to the complexity of these electrochemical systems. Density Functional Theory calculations can be instrumental in supporting and interpreting experimental results. In this work, the results of DFT PDOS calculations of oxygen adsorbed on an Fe(110) surface revealed a hybridised orbital around the Fermi level that explains the origin of the asymmetricoxygen peak in the XPS spectrum. Other more traditional electrochemical models have been developed over the years to improve our understanding and forecasting capabilities of CO2 corrosion, however these models are unable to capture the stochastic nature of the corrosion process which is key to describe stochastic phenomena such as localised corrosion and the formation of the corrosion scale. This work presents the Semi-local Corrosion Approximation, a novel modelling technique that combines a general corrosion electrochemical model with elements of cellular automaton stochastic models to simulate the corrosion process using a 3-dimensional description of the corrosion system. The model predicts the evolution of the physical properties of the corrosion scale which are found to play an important role in the protection of the steel surface. The 3-dimensional analysis of the corrosion scale shows that scales formed under a high precipitation rate may develop localised corrosion as the FeCO3 supersaturation is consumed before the scale fully covers the steel surface.