Analysis of petroleum contaminated soils by spectral modeling and pure response profile recovery of n-hexane
2014
Chakraborty, Somsubhra | Weindorf, David C. | Li, Bin | Ali, Md Nasim | Majumdar, K. | Ray, D.P.
This pilot study compared penalized spline regression (PSR) and random forest (RF) regression using visible and near-infrared diffuse reflectance spectroscopy (VisNIR DRS) derived spectra of 164 petroleum contaminated soils after two different spectral pretreatments [first derivative (FD) and standard normal variate (SNV) followed by detrending] for rapid quantification of soil petroleum contamination. Additionally, a new analytical approach was proposed for the recovery of the pure spectral and concentration profiles of n-hexane present in the unresolved mixture of petroleum contaminated soils using multivariate curve resolution alternating least squares (MCR-ALS). The PSR model using FD spectra (r2 = 0.87, RMSE = 0.580 log10 mg kg−1, and residual prediction deviation = 2.78) outperformed all other models tested. Quantitative results obtained by MCR-ALS for n-hexane in presence of interferences (r2 = 0.65 and RMSE 0.261 log10 mg kg−1) were comparable to those obtained using FD (PSR) model. Furthermore, MCR ALS was able to recover pure spectra of n-hexane.
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