Data analysis of heavy metal pollution in the sea by using principal component analysis and partial least squares regression

Sulo Piepponen, Reijo Lindström

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)

Abstract

Environmental heavy metal pollution in the coastal waters of the Bothnian Sea near the city of Pori was monitored by observations of mussels (Mytilus edulis L.).
The concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb, Sb, Ti, V and Zn in the soft tissues of the mussels and in different fractions of the shells were determined by wet digestion and atomic absorption spectrometry.

Mussel samples were collected at twelve sampling sites at measured distances from the main contamination sources: the local titanium oxide industry and the river Kokemäenjoki. At the same sites, mussels from another area maintained in cages were exposed to the heavy metal uptake for about 2.5 months.
Both the local and caged mussels were analyzed.

The data, consisting of the concentrations of 13 elements, the percentages of shell deformities and the distances from the sources of pollution, were studied by SIMCA and partial least squares (PLS) methods. The shell deformities and the distances from the two pollution sources were treated as dependent variables in PLS. Calculations were made using the data of different fractions alone and of many fractions together. The PLS predictions for the distances were used to estimate the size of the polluted area. Up to 20–40 kilometers from the pollution sources the prediction models fitted well to the measured distances.
The study showed that the elemental variables Fe, Ti and V were most strongly related to the titanium oxide industry and Al, Co, Hg and Mn to the river Kokemäenjoki.

Original languageEnglish
Pages (from-to)163-170
JournalChemometrics and Intelligent Laboratory Systems
Volume7
Issue number1-2
DOIs
Publication statusPublished - 1989
MoE publication typeA1 Journal article-refereed
EventFirst Scandinavian Symposium on Chemometrics - Lappeenranta, Finland
Duration: 6 Oct 19898 Oct 1989

Fingerprint

Heavy Metals
Principal component analysis
Heavy metals
Pollution
Titanium oxides
Rivers
Atomic absorption spectrometry
Industry
Contamination
Tissue
Sampling
Water
titanium dioxide

Cite this

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title = "Data analysis of heavy metal pollution in the sea by using principal component analysis and partial least squares regression",
abstract = "Environmental heavy metal pollution in the coastal waters of the Bothnian Sea near the city of Pori was monitored by observations of mussels (Mytilus edulis L.). The concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb, Sb, Ti, V and Zn in the soft tissues of the mussels and in different fractions of the shells were determined by wet digestion and atomic absorption spectrometry.Mussel samples were collected at twelve sampling sites at measured distances from the main contamination sources: the local titanium oxide industry and the river Kokem{\"a}enjoki. At the same sites, mussels from another area maintained in cages were exposed to the heavy metal uptake for about 2.5 months. Both the local and caged mussels were analyzed.The data, consisting of the concentrations of 13 elements, the percentages of shell deformities and the distances from the sources of pollution, were studied by SIMCA and partial least squares (PLS) methods. The shell deformities and the distances from the two pollution sources were treated as dependent variables in PLS. Calculations were made using the data of different fractions alone and of many fractions together. The PLS predictions for the distances were used to estimate the size of the polluted area. Up to 20–40 kilometers from the pollution sources the prediction models fitted well to the measured distances. The study showed that the elemental variables Fe, Ti and V were most strongly related to the titanium oxide industry and Al, Co, Hg and Mn to the river Kokem{\"a}enjoki.",
author = "Sulo Piepponen and Reijo Lindstr{\"o}m",
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Data analysis of heavy metal pollution in the sea by using principal component analysis and partial least squares regression. / Piepponen, Sulo; Lindström, Reijo.

In: Chemometrics and Intelligent Laboratory Systems, Vol. 7, No. 1-2, 1989, p. 163-170.

Research output: Contribution to journalArticleScientificpeer-review

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AB - Environmental heavy metal pollution in the coastal waters of the Bothnian Sea near the city of Pori was monitored by observations of mussels (Mytilus edulis L.). The concentrations of Al, As, Cd, Co, Cr, Cu, Fe, Hg, Mn, Pb, Sb, Ti, V and Zn in the soft tissues of the mussels and in different fractions of the shells were determined by wet digestion and atomic absorption spectrometry.Mussel samples were collected at twelve sampling sites at measured distances from the main contamination sources: the local titanium oxide industry and the river Kokemäenjoki. At the same sites, mussels from another area maintained in cages were exposed to the heavy metal uptake for about 2.5 months. Both the local and caged mussels were analyzed.The data, consisting of the concentrations of 13 elements, the percentages of shell deformities and the distances from the sources of pollution, were studied by SIMCA and partial least squares (PLS) methods. The shell deformities and the distances from the two pollution sources were treated as dependent variables in PLS. Calculations were made using the data of different fractions alone and of many fractions together. The PLS predictions for the distances were used to estimate the size of the polluted area. Up to 20–40 kilometers from the pollution sources the prediction models fitted well to the measured distances. The study showed that the elemental variables Fe, Ti and V were most strongly related to the titanium oxide industry and Al, Co, Hg and Mn to the river Kokemäenjoki.

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