Non-destructive Spectroscopy combined with chemometrics as a tool for Green Chemical Analysis of environmental samples: A review

Article ID	Journal	Published Year	Pages	File Type
7689023	TrAC Trends in Analytical Chemistry	2016	10 Pages	PDF

Abstract

The design of environmentally friendly analytical techniques and the modification of methods that are in use are important issues to be addressed in Green Analytical Chemistry. Potential applications of non-destructive spectroscopic techniques to achieve these principles are discussed in this review. Special emphasis is placed in environmental samples. Taking into account the current tendency to combine the analysis of environmental samples by non-destructive spectroscopic techniques and chemometrics, the most important applications concerning this task are also compiled. Although multiple objectives are pursued, regression techniques, frequently in combination with infrared spectroscopy, stand out, with around 300 references since 2009. More than half of these publications deal with the design of models to predict properties of soils. Nonetheless, the combination of regression techniques and non-destructive spectroscopy is continuously progressing, and they have been applied, for example, in the analysis of different environmental samples by remote or in-situ multispectral sensors with satisfactory results.

Keywords

ICP-AES ATR MLR PARAFAC GRNN ARIMA MCR-ALS BRT MIR DRIFT LWR LS-SVM BP-ANN k-NN SEM-EDX ED-XRF SML AAS PLS MCR PLS-DA GA-PLS ANN NIR k-nearest neighbour PCA STATIS Cluster analysis inductively coupled plasma atomic emission spectrometry Energy dispersive X-ray fluorescence Diffuse reflectance infrared Fourier transform Attenuated total reflectance Partial least squares discriminant analysis Linear discriminant analysis Parallel factor analysis Factor analysis Principal component analysis LDA least squares support vector machine Partial least squares Boosted regression tree Multivariate curve resolution alternating least squares Multiple linear regression principal component regression Locally weighted regression Generalized regression neural networks artificial neural networks atomic absorption spectrometry inductively coupled plasma mass spectrometry ICP-MS Infrared middle infrared Near infrared Support vector machine SVM PCR Multivariate curve resolution