[Quantitative analysis model of multi-component complex oil spill source based on near infrared spectroscopy]

Area of Science:

• Analytical Chemistry
• Spectroscopy

Context:

• Complex oil spills pose significant environmental challenges.
• Accurate source identification is crucial for effective mitigation.

Purpose:

• To develop and validate a quantitative analysis model for simulated complex oil spill mixtures.
• To assess the efficacy of near infrared spectroscopy (NIR) for component analysis.

Summary:

• Near infrared spectroscopy (NIR) coupled with Fourier transform and partial least squares (PLS) modeling was employed for quantitative analysis of gasoline, diesel, and kerosene mixtures.
• The second derivative preprocessing method proved optimal for spectral data.
• High correlation coefficients (R2 > 0.99) and low root mean square errors of prediction (RMSEP) were achieved, demonstrating model accuracy.

Impact:

• This study validates NIR spectroscopy as a powerful tool for quantitative detection and analysis of components in complex marine oil spill sources.
• Provides a reliable method for environmental monitoring and forensic analysis of oil spills.