| Abstract Scope |
The growing global demand for alternative energy sources has heightened interest in
unconventional petroleum resources such as tar sands. Nigeria’s vast deposits, particularly in Ondo State, remain underutilized due to environmental and technical challenges. This study investigates the environmental impact of tar sand digestion using a laboratory-scale Tar Sand
Digester at the Central Technological and Laboratory Workshop, Obafemi Awolowo University, Nigeria. Tar sands sourced from Agbabu, Ondo State, were analyzed to assess emissions, effluents, and residues generated during digestion. A key innovation of the research is the integration of Artificial Intelligence (AI), specifically Artificial Neural Networks (ANNs), to predict environmental outcomes based on experimental parameters and outputs.
The AI models trained on these data effectively forecasted pollution profiles under different operating conditions. The results demonstrate the potential of AI in
environmental risk assessment, offering a framework for sustainable tar sand exploitation in Nigeria, informing policy, industrial design, and regulatory decision-making. |