A comprehensive review on analytical and equation derived multivariate chemometrics for the accurate interpretation of the degradation of aqueous contaminants

Abstract

Preciseness in pollutant analysis and optimizing a process required to remediate wastewater are essential in environmental engineering. The chemometric approach is used to analyze pollutant molecules from actual samples with maximum accuracy quantitatively. Various calibration models like Principal Component Regression, Partial Least Squares, Cluster analysis, Parallel Factor Analysis, and Artificial Neural Networks are employed to compute the pollutant concentration. In this review, the application of chemometrics in aqueous pollutant degradation processes is explained to understand better how accurate and what kind of information can be extracted from the pollutant degradation processes using chemometrics. The reaction rate-determining ability of Multivariate Curve Resolution–Alternating Least Square, a second-order chemometric model, is explained. Understanding the degradation profiles of a mixture of components and analyzing the by-product evolution are benefits of employing chemometrics. This review describes studies where chemometrics and response surface methodology-based techniques are used to gain insights into process optimization and resolve issues on the accurate determination of pollutant concentration profiles. Suitable examples of advanced oxidation methods, namely photocatalytic degradation, and gamma-ray mediated pollutant deterioration, are discussed to understand better the application of Canonical and Ridge analysis. This review gives the readers a good view of various applications of chemometrics in accurate assessment of pollutants in multi-component systems and process optimization of pollutant degradation.