Oil spill identification by near-infrared spectroscopy

Petroleum oil spill happens occasionally at sea. It's important to differentiate the exact products in order to carry out following actions to decrease harmfulness. In the present study, a rapid oil spill identification method by near infrared spectroscopy coupled with pattern recognition techniques is proposed. 56 simulated spilled oils of gasoline, diesel fuel and lubricating oil in marine were chosen to develop the method. Organic reagent of CCl4 was used to extract the oil. Pattern recognition techniques were established by principal component analysis (PCA) coupled with Mahalanobis' distance with the multiplicative signal correction (MSC) and Norris first derivative pretreatment. The study shows that PCA technique is a useful method to extract the main characteristics, and Mahalanobis' distance is an ellipsoidal boundary that circumscribes a data cluster. And oil spill samples with concentration above 0.4 muL(.)mL(-1) can be successfully identified by the method. The developed technique could be further applied to the identification of spilled oil in marine.