Environmental Toxicology of Petroleum Sludge at Warri Refinery Environment: Quantitative Risk Assessment and Predictive Modeling Using Artificial Intelligence
Domaine:
environment and energyType de record:
paper
Créateur:
ErnUboUdeAka
Éditeur:
Nem
Hôte:
Petroleum sludge is one of the most persistent byproducts of crude oil refining, posing a significant environmental problem due to its complex composition of hydrocarbons, polycyclic aromatic hydrocarbons (PAHs), and heavy metals. This paper examined the ecological toxicology of petroleum sludge at the Warri Refining and Petrochemical Company (WRPC), Delta State, Nigeria, through empirical, computational, and biological analyses, coupled with the Systems Theory of Environmental Toxicology. The primary objective was to describe the sludge composition, assess the human and ecological risks, and develop artificial intelligence (AI)-driven predictive models to enhance environmental management. Unlike previous refinery toxicology studies that focus solely on chemical characterization or risk estimation, this study uniquely integrates field data, quantitative risk assessment, and multi-model AI prediction to address the lack of predictive environmental intelligence in refinery-impacted ecosystems.
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