Zahra Sohrabizadeh, Hamid Sodaeizadeh, Mohammad Ali Hakimzadeh, Ruhollah Taghizadeh-Mehrjardi, Mohammad Javad Ghanei Bafghi
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A statistical approach to study the spatial heavy metal distribution in soils in the Kushk Mine, Iran
The present study was conducted for the spatial distribution and concentration evaluation of heavy metals, including Cu, Cd, Mn, Fe, Zn, and Pb, within 102 soil samples collected from Kushk Mine in Bafgh, Iran. This work employed hierarchical clustering analysis (HCA), principal component analysis (PCA), and spatial distribution patterns, to perform element distribution evaluation within the area. The distributions of heavy metals in the entire area were exhibited in the form of maps. The average concentrations of Cd, Cu, Mn, Fe, Zn, and Pb were found to be 0.39, 0.26, 5.3, 4.1, 51.9, and 40.9 mg.kg−1, respectively. Based on the PCA and HCA findings, the heavy metals were divided into two groups. The first group included Pb, Cd, Zn, and Cu. In the first group, altered threshold-surpassing anthropogenic and lithogenic pollution was found to be the main factor accounting for Pb and Zn. The second group involved Fe and Mn, which could be impacted by either anthropogenic and lithogenic factors. Furthermore, the geo-statistical results demonstrated higher contents of the heavy metals in the south of the mine and in the vicinity of the mine tailings. It may be concluded from the results that the heavy metal contents of the area are impacted by anthropogenic and lithogenic factors.
Geoscience Data JournalGEOSCIENCES, MULTIDISCIPLINARYMETEOROLOGY-METEOROLOGY & ATMOSPHERIC SCIENCES
CiteScore
5.90
自引率
9.40%
发文量
35
审稿时长
4 weeks
期刊介绍:
Geoscience Data Journal provides an Open Access platform where scientific data can be formally published, in a way that includes scientific peer-review. Thus the dataset creator attains full credit for their efforts, while also improving the scientific record, providing version control for the community and allowing major datasets to be fully described, cited and discovered.
An online-only journal, GDJ publishes short data papers cross-linked to – and citing – datasets that have been deposited in approved data centres and awarded DOIs. The journal will also accept articles on data services, and articles which support and inform data publishing best practices.
Data is at the heart of science and scientific endeavour. The curation of data and the science associated with it is as important as ever in our understanding of the changing earth system and thereby enabling us to make future predictions. Geoscience Data Journal is working with recognised Data Centres across the globe to develop the future strategy for data publication, the recognition of the value of data and the communication and exploitation of data to the wider science and stakeholder communities.