A Review on Advancement in Technological Innovation of Crude Oil Spill Identification and Remediation

Abstract

Petroleum spills constitute one of the gravest environmental challenges confronting marine and terrestrial ecosystems worldwide, carrying substantial economic and social ramifications. Although spill frequency has shown considerable decline in recent decades with incidents exceeding 700 tonnes decreasing by roughly 90% since 1970, the persistent threat of catastrophic events remains evident, exemplified by the 2010 Deepwater Horizon incident that discharged approximately 600,000 tonnes of petroleum into Gulf of Mexico waters. This review examines the evolutionary trajectory of technological innovations spanning historical, contemporary, and emerging approaches to oil spill detection and remediation. Detection methodologies have progressed from conventional remote sensing techniques toward sophisticated integrated multi-sensor platforms incorporating Synthetic Aperture Radar (SAR), UAV-mounted hyperspectral imaging, fluorescence-based imaging coupled with deep learning algorithms, and artificial intelligence-enabled data synthesis. Remediation strategies have similarly advanced, with conventional mechanical and chemical approaches now complemented by emerging biotechnological solutions. Particular emphasis is placed on next-generation sorbent materials demonstrating remarkable performance metrics, including polycaprolactone-based porous sorbents achieving absorption capacities of 45 g/g with reusability exceeding 15 cycles, alongside biochar-supported Fe₃O₄ nanoparticles enabling enhanced biodegradation capabilities.