E-ISSN 0331-8753 | ISSN 0794-5698
 

Original Research 


Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria

Girgisu Shehu, Isa Baba Koki.

Abstract
Multivariate statistical techniques such as principal component analysis (PCA), factor analysis (FA), and hierarchical cluster analysis (HCA) were utilized for the evaluation of metal distribution and variations in the soil at Awwal mining site. PCA was used to determine a reduced number of three principal components (PC) indicating up to 82 % of the total variation in the soil samples. The result of FA justifies the results of the PCA obtained. HCA classified the soil samples in the sites into two clusters, with cluster one having the higher metal levels, while cluster two had low metal levels but characterized with dominant toxic heavy metals (As and Pb). The results of the multivariate analysis showed that natural percentage abundance in soil and mineral composition of the mining ores were the main sources of the metals under study. Due to high metal levels in the soils, disposal and management of the mining waste/tailings and rehabilitation of the mining site after closure of mining should be done with care and caution to avoid leaching of the toxic metals to surface and underground water for the health and safety of the neighboring community.

Key words: Soil, Metals, Mining, Multivariate analysis, Awwal


 
ARTICLE TOOLS
Abstract
PDF Fulltext
Print this article Print this Article
How to cite this articleHow to cite this article
Citation Tools
Related Records
 Articles by Girgisu Shehu
Articles by Isa Baba Koki
on Google
on Google Scholar
Article Statistics
 Viewed: 833
Downloaded: 23
Cited: 0


How to Cite this Article
Pubmed Style

Shehu G, Koki IB. Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nig. J. Basic Appl. Sci.. 2019; 27(1): 17-24. doi:10.4314/njbas.v27i1.3


Web Style

Shehu G, Koki IB. Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. www.njbas-udus.com/?mno=274169 [Access: July 24, 2019]. doi:10.4314/njbas.v27i1.3


AMA (American Medical Association) Style

Shehu G, Koki IB. Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nig. J. Basic Appl. Sci.. 2019; 27(1): 17-24. doi:10.4314/njbas.v27i1.3



Vancouver/ICMJE Style

Shehu G, Koki IB. Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nig. J. Basic Appl. Sci.. (2019), [cited July 24, 2019]; 27(1): 17-24. doi:10.4314/njbas.v27i1.3



Harvard Style

Shehu, G. & Koki, . I. B. (2019) Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nig. J. Basic Appl. Sci., 27 (1), 17-24. doi:10.4314/njbas.v27i1.3



Turabian Style

Shehu, Girgisu, and Isa Baba Koki. 2019. Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nigerian Journal of Basic and Applied Sciences, 27 (1), 17-24. doi:10.4314/njbas.v27i1.3



Chicago Style

Shehu, Girgisu, and Isa Baba Koki. "Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria." Nigerian Journal of Basic and Applied Sciences 27 (2019), 17-24. doi:10.4314/njbas.v27i1.3



MLA (The Modern Language Association) Style

Shehu, Girgisu, and Isa Baba Koki. "Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria." Nigerian Journal of Basic and Applied Sciences 27.1 (2019), 17-24. Print. doi:10.4314/njbas.v27i1.3



APA (American Psychological Association) Style

Shehu, G. & Koki, . I. B. (2019) Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria. Nigerian Journal of Basic and Applied Sciences, 27 (1), 17-24. doi:10.4314/njbas.v27i1.3