Model‐centric optimisation of biochemical remediation of petroleum hydrocarbon contaminated soil

Abstract In this preliminary research investigation, we introduce a multifactorial approach aimed at optimizing the biochemical remediation of petroleum hydrocarbon (PH) polluted soil. The development of these optimizations was determined after solving the equation set. Moreover, we specified the quantitative correlation between the soil treatment aspects and remediation efficiency by the use of real‐world environmental data from the Klaipeda Oil Terminal, Lithuania. The reaction retention time (RTT) and aeration periodicity were the primary aspects affecting soil fertilization and frequency of microbial addition. Over a 2‐month period, remediation efficiency peaked at 99.99%. The study outcomes suggest that the recommended framework may be used to generalize more rapid biochemical degradation of PHs in polluted soil, moving from laboratory‐scale processes to the field (landfill‐polluted soil) at more than 95% process effectiveness. The accuracy of the formulated framework can be used to arrive at evidence‐based decisions concerning extensive landfill pollution management by estimating contaminant loads and soil‐related treatment aspects.