Diagnostic features emerging in near-infrared reflectance spectroscopy for low petroleum hydrocarbon pollution after spectral subtraction.

Diagnostic features in near-infrared reflectance spectroscopy (NIRS) are the foundation of knowledge-based approach of petroleum hydrocarbon determination. However, a significant challenge arises when analyzing samples with low levels of petroleum hydrocarbon pollution, as they often lack distinctive diagnostic features in their sample NIRS spectra, limiting the effectiveness of this approach. To address this issue, we have developed a technical workflow for diagnostic spectrum construction and parameterization based on spectral subtraction. This method was applied on a set of NIRS spectra from soil samples that were contaminated with petroleum hydrocarbons (ranged between 178 and 1716 mg/kg of total petroleum hydrocarbon). Then two diagnostic features for low-level petroleum hydrocarbon pollution were found: (1) An overall downward concave emerged on diagnostic spectrum within both 2290-2370 nm and 1700-1780 nm for all low pollution levels even below 200 mg/kg; (2) An indicative pattern of asymmetric "W-shaped" double absorption valley occurred for those exceeding 1000 mg/kg, and its valleys located near 2310 nm, 2348 nm or 1727 nm, 1762 nm stably. These two features on diagnostic spectrum could be parameterized to detect, and the detection limit was at least about 10-50 times lower than that based on sample spectrum. These findings update our understanding on the detectability of spectral response from low petroleum hydrocarbon pollution, and widely extend the application of knowledge-based NIRS approach in either field detection or remote sensing identification for environmental management.