Laser induced breakdown spectroscopy and characterization of environmental matrices utilizing multivariate chemometrics
Date
2013Author
Mukhono, P.M.
Angeyo, K.H.
Dehayem-Kamadjeu, A.
Kaduki, K.A.
Type
ArticleLanguage
enMetadata
Show full item recordAbstract
We exploited multivariate chemometric methods to reduce the spectral complexity and to retrieve trace
heavy metal analyte concentration signatures directly from the LlBS spectra as well as. to extract their latent
characteristics in two important environmental samples i.e. soils and rocks from a geothermal field lying in a
high background radiation area (HBRA). As. Cr, Cu. Pb and Ti were modeled for direct trace (quantitative)
analysis using partial least squares (PLS) and artificial neural networks (ANNs). PLS performed better in
soils than in rocks; the use of ANN improved the accuracies in rocks because ANNs are more robust than
PLS at modeling spectral non-linearities and correcting matrix effects. The predicted trace metal profiles together
with atomic and molecular signatures acquired using single ablation in the 200-545 nm spectral
range were utilized to successfully classify and identify the soils and rocks with regard to whether they
were derived from (i) a high background radiation area (HBRA)-geothermal. (ii) HBRA-non-geothermal or
(iii) normal background radiation area (NBRA)-geothermal field using principal components analysis
(PCA) and soft independent modeling of class analogy (SIMCA).