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Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River

Authorized Users Only
2016
Authors
Crnković, Dragan
Antanasijević, Davor
Pocajt, Viktor
Perić-Grujić, Aleksandra
Antonović, Dušan
Ristić, Mirjana
Article (Published version)
Metadata
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Abstract
The aim of this study was to evaluate the quality of freshwater sediments by means of three chemometric techniques for multi-criteria analysis and decision: self-organizing network (SON), self-organizing map (SOM) and PROMETHEE&GAIA (Preference Ranking Organization Method for Enrichment Evaluation with Geometrical Analysis for Interactive Aid). Selected chemometric techniques were applied to the results of Pb, Cd, Zn, Cu, Ni, Cr, Hg and As content in thirty Danube and fourteen Sava river sediment samples from Serbia. The potential toxicity of sediments was estimated using Probable Effect Concentrations quotients (mean PEC-Q). According to the SON analysis the Danube sediment samples were divided into three classes, Class I (mean PEC-Q range 0.27-0.51), Class II (mean PEC-Qrange 0:50-0.70), and Class III (mean PEC-Qrange 0.77-0.97), while the Sava samples were divided into two classes, Class II (two samples, mean PEC-Qvalues 0.65 and 0.69) and Class III (mean PEC-Q range 0.69-1.00). Usi...ng the SOM cluster analysis, both Danube and Sava sediment samples were classified into five subclusters, on the basis of the metal concentration level and further ranked into three levels (for remediation, moderately polluted and not polluted) by the use of multi-criteria ranking PROMETHEE method. Graphical presentation of the results obtained by PROMETHEE method using GAIA descriptive tool has provided an insight into the distribution of examined elements in sediments and has shown a significant correlation between some elements. On the basis of the results obtained, it has been concluded that the proposed chemometric approach could provide useful information in the sediment quality assessment.

Keywords:
Heavy metals / Classification / Kohonen neural networks / PROMETHEE&GAIA
Source:
Catena, 2016, 144, 11-22
Publisher:
  • Elsevier, Amsterdam
Funding / projects:
  • Development and Application of Methods and Materials for Monitoring New Organic Contaminants, Toxic Compounds and Heavy Metals (RS-172007)

DOI: 10.1016/j.catena.2016.04.025

ISSN: 0341-8162

WoS: 000379375900002

Scopus: 2-s2.0-84979288115
[ Google Scholar ]
13
12
URI
http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3274
Collections
  • Radovi istraživača / Researchers’ publications (TMF)
Institution/Community
Tehnološko-metalurški fakultet
TY  - JOUR
AU  - Crnković, Dragan
AU  - Antanasijević, Davor
AU  - Pocajt, Viktor
AU  - Perić-Grujić, Aleksandra
AU  - Antonović, Dušan
AU  - Ristić, Mirjana
PY  - 2016
UR  - http://TechnoRep.tmf.bg.ac.rs/handle/123456789/3274
AB  - The aim of this study was to evaluate the quality of freshwater sediments by means of three chemometric techniques for multi-criteria analysis and decision: self-organizing network (SON), self-organizing map (SOM) and PROMETHEE&GAIA (Preference Ranking Organization Method for Enrichment Evaluation with Geometrical Analysis for Interactive Aid). Selected chemometric techniques were applied to the results of Pb, Cd, Zn, Cu, Ni, Cr, Hg and As content in thirty Danube and fourteen Sava river sediment samples from Serbia. The potential toxicity of sediments was estimated using Probable Effect Concentrations quotients (mean PEC-Q). According to the SON analysis the Danube sediment samples were divided into three classes, Class I (mean PEC-Q range 0.27-0.51), Class II (mean PEC-Qrange 0:50-0.70), and Class III (mean PEC-Qrange 0.77-0.97), while the Sava samples were divided into two classes, Class II (two samples, mean PEC-Qvalues 0.65 and 0.69) and Class III (mean PEC-Q range 0.69-1.00). Using the SOM cluster analysis, both Danube and Sava sediment samples were classified into five subclusters, on the basis of the metal concentration level and further ranked into three levels (for remediation, moderately polluted and not polluted) by the use of multi-criteria ranking PROMETHEE method. Graphical presentation of the results obtained by PROMETHEE method using GAIA descriptive tool has provided an insight into the distribution of examined elements in sediments and has shown a significant correlation between some elements. On the basis of the results obtained, it has been concluded that the proposed chemometric approach could provide useful information in the sediment quality assessment.
PB  - Elsevier, Amsterdam
T2  - Catena
T1  - Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River
EP  - 22
SP  - 11
VL  - 144
DO  - 10.1016/j.catena.2016.04.025
ER  - 
@article{
author = "Crnković, Dragan and Antanasijević, Davor and Pocajt, Viktor and Perić-Grujić, Aleksandra and Antonović, Dušan and Ristić, Mirjana",
year = "2016",
abstract = "The aim of this study was to evaluate the quality of freshwater sediments by means of three chemometric techniques for multi-criteria analysis and decision: self-organizing network (SON), self-organizing map (SOM) and PROMETHEE&GAIA (Preference Ranking Organization Method for Enrichment Evaluation with Geometrical Analysis for Interactive Aid). Selected chemometric techniques were applied to the results of Pb, Cd, Zn, Cu, Ni, Cr, Hg and As content in thirty Danube and fourteen Sava river sediment samples from Serbia. The potential toxicity of sediments was estimated using Probable Effect Concentrations quotients (mean PEC-Q). According to the SON analysis the Danube sediment samples were divided into three classes, Class I (mean PEC-Q range 0.27-0.51), Class II (mean PEC-Qrange 0:50-0.70), and Class III (mean PEC-Qrange 0.77-0.97), while the Sava samples were divided into two classes, Class II (two samples, mean PEC-Qvalues 0.65 and 0.69) and Class III (mean PEC-Q range 0.69-1.00). Using the SOM cluster analysis, both Danube and Sava sediment samples were classified into five subclusters, on the basis of the metal concentration level and further ranked into three levels (for remediation, moderately polluted and not polluted) by the use of multi-criteria ranking PROMETHEE method. Graphical presentation of the results obtained by PROMETHEE method using GAIA descriptive tool has provided an insight into the distribution of examined elements in sediments and has shown a significant correlation between some elements. On the basis of the results obtained, it has been concluded that the proposed chemometric approach could provide useful information in the sediment quality assessment.",
publisher = "Elsevier, Amsterdam",
journal = "Catena",
title = "Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River",
pages = "22-11",
volume = "144",
doi = "10.1016/j.catena.2016.04.025"
}
Crnković, D., Antanasijević, D., Pocajt, V., Perić-Grujić, A., Antonović, D.,& Ristić, M.. (2016). Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River. in Catena
Elsevier, Amsterdam., 144, 11-22.
https://doi.org/10.1016/j.catena.2016.04.025
Crnković D, Antanasijević D, Pocajt V, Perić-Grujić A, Antonović D, Ristić M. Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River. in Catena. 2016;144:11-22.
doi:10.1016/j.catena.2016.04.025 .
Crnković, Dragan, Antanasijević, Davor, Pocajt, Viktor, Perić-Grujić, Aleksandra, Antonović, Dušan, Ristić, Mirjana, "Unsupervised classification and multi-criteria decision analysis as chemometric tools for the assessment of sediment quality: A case study of the Danube and Sava River" in Catena, 144 (2016):11-22,
https://doi.org/10.1016/j.catena.2016.04.025 . .

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