Integrated approach of heavy metal evaluation using geostatistical and pollution assessment index in soil of bauxite mining area

Nur Shuhada Tajudin and Mazidah Zulkifli and Mohd Fuad Miskon and Mohamad Izzuddin Anuar and Zulkifli Hashim and Fikriah Faudzi and Nurul Mayzaitul Azwa Jamaluddin. (2022) Integrated approach of heavy metal evaluation using geostatistical and pollution assessment index in soil of bauxite mining area. Pertanika Journal of Science & Technology (Malaysia), 30 (2). 1545 -1566. ISSN 2231-8526

Heavy metals contamination in soil is one of the global issues, posing a threat not just to the environment but also to human health. Identifying the source and distribution of heavy metal pollutants around mining areas can provide a scientific basis for future environmental control. Distributions of the heavy metals (Cd, Cr, As, and Ni) in this study were evaluated using descriptive and multivariate statistics and further described using a geostatistical approach and pollution indices. The total content of Cr, Cd, and Ni in surface soil was observed with a higher concentration level according to the Dutch target values and the 95% Investigation Levels determined for Malaysia soil. Statistical analyses, geostatistics, and GIS mapping suggested that Cd, Cr, and Ni were derived mainly from anthropogenic sources, including mining and agricultural activities, while As could be derived from lithogenic and anthropogenic sources. Geoaccumulation index analysis demonstrated that the contamination that occurred with Cd posed the greatest risk of contamination, followed by Cr, Ni, and As. A spatial interpolated map showed a higher concentration of heavy metals in the vicinity of the mining area. These findings highlight the effectiveness of principal component analysis, geostatistics, and geospatial analyses in evaluating heavy metal contents in the study area. The obtained results could be used by authorities to identify areas requiring remediation management and establish scientific baseline data related to soil quality.

Full text available from: Official URL: http://www.pertanika.upm.edu.my/resources/files/Pe...

Abstract

Heavy metals contamination in soil is one of the global issues, posing a threat not just to the environment but also to human health. Identifying the source and distribution of heavy metal pollutants around mining areas can provide a scientific basis for future environmental control. Distributions of the heavy metals (Cd, Cr, As, and Ni) in this study were evaluated using descriptive and multivariate statistics and further described using a geostatistical approach and pollution indices. The total content of Cr, Cd, and Ni in surface soil was observed with a higher concentration level according to the Dutch target values and the 95% Investigation Levels determined for Malaysia soil. Statistical analyses, geostatistics, and GIS mapping suggested that Cd, Cr, and Ni were derived mainly from anthropogenic sources, including mining and agricultural activities, while As could be derived from lithogenic and anthropogenic sources. Geoaccumulation index analysis demonstrated that the contamination that occurred with Cd posed the greatest risk of contamination, followed by Cr, Ni, and As. A spatial interpolated map showed a higher concentration of heavy metals in the vicinity of the mining area. These findings highlight the effectiveness of principal component analysis, geostatistics, and geospatial analyses in evaluating heavy metal contents in the study area. The obtained results could be used by authorities to identify areas requiring remediation management and establish scientific baseline data related to soil quality.

[error in script]

Item Type:	Article
AGROVOC Term:	soil pollution
AGROVOC Term:	heavy metals
AGROVOC Term:	geostatistics
AGROVOC Term:	spatial data
AGROVOC Term:	soil sampling
AGROVOC Term:	soil properties
AGROVOC Term:	pattern recognition
AGROVOC Term:	soil quality
AGROVOC Term:	soil treatment
Geographical Term:	Malaysia
Uncontrolled Keywords:	Bauxite mining, geoaccumulation index, GIS, heavy metals, semivariogram
Depositing User:	Ms. Azariah Hashim
Date Deposited:	12 Nov 2024 04:09
Last Modified:	12 Nov 2024 04:09
URI:	http://webagris.upm.edu.my/id/eprint/1766

Actions (login required)

View Item