Assessment of heavy metals and nutrients availability in oil palm plantation effected by bauxite mining using geostatistical and multivariate analyses

The study aimed at evaluation of soil heavy metals in oil palm plantation and selected nutrients availability effected by mining. It was investigated using multivariate and geostatistical analyses followed by assessment using environmental indices. Samples were collected from both mining and o...

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Main Authors: Zulkifli, Mazidah, A, Amalyn, Muhamad Tajudin, Nur Shuhada, Miskon, Mohd Fuad, Faudzi, Fikriah, Mohamad Anuar, Izzuddin
格式: Conference or Workshop Item
语言:English
English
出版: IOP Publishing 2022
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在线阅读:http://irep.iium.edu.my/99784/2/99784_Assessment%20of%20heavy%20metals%20and%20nutrients.pdf
http://irep.iium.edu.my/99784/3/99784_Assessment%20of%20heavy%20metals%20and%20nutrients_Scopus.pdf
http://irep.iium.edu.my/99784/
https://doi.org/10.1088/1755-1315/1064/1/012002
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总结:The study aimed at evaluation of soil heavy metals in oil palm plantation and selected nutrients availability effected by mining. It was investigated using multivariate and geostatistical analyses followed by assessment using environmental indices. Samples were collected from both mining and oil palm cultivated area, prepared, and analyzed using ICPMS. Semi-variogram and kriging were done by using GS+ and ArcGIS 10.8, respectively. Content of Cu, Cr and Zn were higher compared to the Dutch target values and the 95% ‘Investigation Levels’ determined for Malaysia soil, while Pb showed a lower value. Analysis of Principal Component suggested that the heavy metals were from one source of contamination, particularly the mining activities and long-term agricultural practices. Geostatistics analyses revealed that Zn, Cu, Pb and Fe confront to a strong spatial dependence structure and in line with multivariate and statistical analysis, except for Cr, which had a moderate spatial dependence. Geoaccumulation Index demonstrated contamination occurred in the order of Cr>Cu>Fe>Zn>Ni>Pb. The heavy metals contamination has impacted the micronutrients contents as lower K, Ca and Mg were observed. These findings highlight that combining multivariate and geostatistical analysis can be valuable tools for assessing environmental contamination.