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
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2016
Authors
Crnković, DraganAntanasijević, Davor

Pocajt, Viktor

Perić-Grujić, Aleksandra

Antonović, Dušan
Ristić, Mirjana

Article (Published version)

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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&GAIASource:
Catena, 2016, 144, 11-22Publisher:
- Elsevier, Amsterdam
Funding / projects:
DOI: 10.1016/j.catena.2016.04.025
ISSN: 0341-8162
WoS: 000379375900002
Scopus: 2-s2.0-84979288115
Institution/Community
Tehnološko-metalurški fakultetTY - 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 . .