A multivariate calibration approach for determination of petroleum hydrocarbons in water by means of IR spectroscopy

Abstract

The goal of this paper is the development of a multivariate calibration method for the quantitative determination of petroleum hydrocarbons in water and waste water by using FT-IR spectroscopy and PLS as a regression method to improve the results attained at the present time through the univariate standard method. In order to evaluate the performance of the regression model, four experimental responses obtained from an independent validation set prepared with spiked samples were examined: Root mean square error of prediction (RMSEP), average recovery, standard deviation, and relative standard deviation. In order to compare final results, the univariate model was developed together with the multivariate approach. The results show that the multivariate calibration method outperforms the univariate standard method. The accuracy of the results, capability of detection, and the high index of recovery obtained show that a multivariate calibration approach for the determination of petroleum hydrocarbons in water and waste water by means of IR spectroscopy can be seen as a very promising option to improve the current univariate standard method.

Deconvolution of petroleum mixtures using mid-FTIR analysis and non-negative matrix factorization

“…IR) may be carried out using the classical multivariate calibration approach. Following this supervised approach, a model can be developed based on 'known' training samples and afterwards applied to the 'unknowns' [3]. Yet this procedure is tedious, time-consuming and expensive, due to the required numerous preliminary measurements.…”

Study of Distillation Temperature Curves from Brazilian Crude Oil by 1H Nuclear Magnetic Resonance Spectroscopy in Association with Partial Least Squares Regression

“…Thus, the chemometric approach is useful to overcome these drawbacks. Taking into account crude oil physicochemical property determination, the most common scientific reports found in the literature consider near-infrared (NIR) and medium-infrared (MIR) spectroscopy in association with partial least squares (PLS) regression as a powerful alternative methodology. − Besides that, nuclear magnetic resonance (NMR) spectroscopy has also gained prominence in petroleum characterization. − …”