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Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant

The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarograp...

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Autores principales: Zamani, Abbas Ali, Yaftian, Mohammad Reza, Parizanganeh, Abdolhossein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561054/
https://www.ncbi.nlm.nih.gov/pubmed/23369182
http://dx.doi.org/10.1186/1735-2746-9-29
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author Zamani, Abbas Ali
Yaftian, Mohammad Reza
Parizanganeh, Abdolhossein
author_facet Zamani, Abbas Ali
Yaftian, Mohammad Reza
Parizanganeh, Abdolhossein
author_sort Zamani, Abbas Ali
collection PubMed
description The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area.
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spelling pubmed-35610542013-02-05 Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant Zamani, Abbas Ali Yaftian, Mohammad Reza Parizanganeh, Abdolhossein Iranian J Environ Health Sci Eng Research Article The contamination of groundwater by heavy metal ions around a lead and zinc plant has been studied. As a case study groundwater contamination in Bonab Industrial Estate (Zanjan-Iran) for iron, cobalt, nickel, copper, zinc, cadmium and lead content was investigated using differential pulse polarography (DPP). Although, cobalt, copper and zinc were found correspondingly in 47.8%, 100.0%, and 100.0% of the samples, they did not contain these metals above their maximum contaminant levels (MCLs). Cadmium was detected in 65.2% of the samples and 17.4% of them were polluted by this metal. All samples contained detectable levels of lead and iron with 8.7% and 13.0% of the samples higher than their MCLs. Nickel was also found in 78.3% of the samples, out of which 8.7% were polluted. In general, the results revealed the contamination of groundwater sources in the studied zone. The higher health risks are related to lead, nickel, and cadmium ions. Multivariate statistical techniques were applied for interpreting the experimental data and giving a description for the sources. The data analysis showed correlations and similarities between investigated heavy metals and helps to classify these ion groups. Cluster analysis identified five clusters among the studied heavy metals. Cluster 1 consisted of Pb, Cu, and cluster 3 included Cd, Fe; also each of the elements Zn, Co and Ni was located in groups with single member. The same results were obtained by factor analysis. Statistical investigations revealed that anthropogenic factors and notably lead and zinc plant and pedo-geochemical pollution sources are influencing water quality in the studied area. BioMed Central 2012-12-17 /pmc/articles/PMC3561054/ /pubmed/23369182 http://dx.doi.org/10.1186/1735-2746-9-29 Text en Copyright ©2012 Zamani et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zamani, Abbas Ali
Yaftian, Mohammad Reza
Parizanganeh, Abdolhossein
Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title_full Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title_fullStr Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title_full_unstemmed Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title_short Multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
title_sort multivariate statistical assessment of heavy metal pollution sources of groundwater around a lead and zinc plant
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3561054/
https://www.ncbi.nlm.nih.gov/pubmed/23369182
http://dx.doi.org/10.1186/1735-2746-9-29
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