Vis-NIR Reflectance Spectroscopy and PLSR to Predict PCB Content in Severely Contaminated Soils: A Perspective Approach

Abstract

Soil reclamation from polychlorinated biphenyls (PCBs) requires careful analysis in terms of their concentrations and spatial distribution. Conventional laboratory analysis, even if providing the careful evaluation of PCBs, is costly and time-consuming. Therefore, rapid and cost-effective techniques to replace traditional analytical approaches are required. The utility of visible-near infrared (vis-NIR) reflectance spectroscopy in conjunction with partial least square regression (PLSR) analysis was evaluated in this study. Spectral reflectance was measured in the laboratory on 28 soil samples collected in a highly contaminated area of southern Italy and chemically analysed to determine eighteen PCB congeners, their sum (PCBs18), and extractable organic halogen content (EOX). Spectroscopic data were pre-processed prior to data analysis by combining different methods. Using PLSR analysis, significant relationships were observed between the predicted and the measured content of PCBs18, EOX, and the percentage of several isomeric classes of PCBs. Although rigorous models could not be calibrated, due to the limited number of samples, the preliminary results of this study demonstrated that vis-NIR reflectance spectroscopy, coupled with PLSR, can be considered a promising method for a rapid and cost-effective prediction of PCBs.