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Impact of River Water and Bottom Sediment Pollution on Accumulation of Metal(loid)s and Arsenic Species in the Coastal Plants Stuckenia pectinata L., Galium aparine L., and Urtica dioica L.: A Chemometric and Environmental Study.

Authors
  • Jabłońska-Czapla, Magdalena1
  • Zerzucha, Piotr2
  • Grygoyć, Katarzyna3
  • 1 Institute of Environmental Engineering of the Polish Academy of Sciences, 34 M. Skłodowska-Curie Street, 41-819, Zabrze, Poland. [email protected] , (Poland)
  • 2 Faculty of Philosophy, The Pontifical University of John Paul II, 9 Kanonicza Street, 31-002, Kraków, Poland. , (Poland)
  • 3 Institute of Environmental Engineering of the Polish Academy of Sciences, 34 M. Skłodowska-Curie Street, 41-819, Zabrze, Poland. , (Poland)
Type
Published Article
Journal
Archives of environmental contamination and toxicology
Publication Date
Jul 01, 2020
Volume
79
Issue
1
Pages
60–79
Identifiers
DOI: 10.1007/s00244-020-00727-w
PMID: 32285162
Source
Medline
Language
English
License
Unknown

Abstract

The role of water and bottom sediment pollution of a river subjected to a strong industrial anthropo-pressure in coastal plants was investigated. The work presented the influence of polluted environment on accumulation of metal(loid)s (including arsenic and its species) in Stuckenia pectinata L., Galium aparine L., and Urtica dioica L. The study provided important information on the contents of organic and inorganic arsenic species in selected plants and their response to heavy metal and arsenic contamination. The As(III), As(V), AB (arsenobetaine), MMA (monomethylarsonic acid), and DMA (dimethylarsinic acid) ions were successfully separated on the Hamilton PRP-X100 column with high-performance liquid chromatography-inductively coupled plasma-mass spectrometry (HPLC-ICP-MS) techniques. The Pollution Load Index and geo-accumulation Index (Igeo) values clearly indicate significant pollution of the examined ecosystem with heavy metals. The chemometric analysis with the concepts of (Dis)similarity Analysis, Cluster Analysis, and Principal Component Analysis helped to visualize the variability of the As species concentrations and to analyse correlations between sampling point locations and analyte contents.

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