This study presents a novel approach to optimizing bioventing processes through the development of a comprehensive three-dimensional mathematical model. Bioventing, a widely used remediation technique for soil and groundwater contaminated with petroleum hydrocarbons, relies on the stimulation of indigenous microbial populations to degrade contaminants. However, its efficacy is often limited by various factors, including the heterogeneity of subsurface conditions. To address this challenge, our model integrates key parameters such as soil properties, airflow dynamics, microbial activity and contaminant transport in a three-dimensional framework. Through rigorous calibration and validation against experimental data, the model offers a robust tool for predicting and optimizing bioventing performance under diverse environmental conditions. Implementation of this model can enhance the efficiency and cost-effectiveness of bioventing as a sustainable remediation strategy for contaminated sites.
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