ArticleData in brief2017
Geostatistical exploration of dataset assessing the heavy metal contamination in Ewekoro limestone, Southwestern Nigeria.
Article in Data in brief, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- A Study of Noise Pollution Measurements and Possible Effects on Public Health in Ota Metropolis, Nigeria.Open access Macedonian journal of medical sciences · 2019Article
- Geoelectrical resistivity data set for characterising crystalline basement aquifers in Basiri, Ado-Ekiti, southwestern Nigeria.Data in brief · 2018Article
- Electrical resistivity imaging (ERI) data for characterising crystalline basement structures in Abeokuta, southwestern Nigeria.Data in brief · 2018Article
- Water quality assessment for groundwater around a municipal waste dumpsite.Data in brief · 2018Article
- Data on the thermal properties of soil and its moisture content.Data in brief · 2018Article
- Dataset on ground radiometric survey in part of the Eastern Dahomey Basin, SW Nigeria.Data in brief · 2017Article
- Geoexploration of radioelement's datasets in a flood plain of crystalline bedrock.Data in brief · 2017Article
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Authors and funding
3 authors.
Funding
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Abstract
The dataset for this article contains geostatistical analysis of heavy metals contamination from limestone samples collected from Ewekoro Formation in the eastern Dahomey basin, Ogun State Nigeria. The samples were manually collected and analysed using Microwave Plasma Atomic Absorption Spectrometer (MPAS). Analysis of the twenty different samples showed different levels of heavy metals concentration. The analysed nine elements are Arsenic, Mercury, Cadmium, Cobalt, Chromium, Nickel, Lead, Vanadium and Zinc. Descriptive statistics was used to explore the heavy metal concentrations individually. Pearson, Kendall tau and Spearman rho correlation coefficients was used to establish the relationships among the elements and the analysis of variance showed that there is a significant difference in the mean distribution of the heavy metals concentration within and between the groups of the 20 samples analysed. The dataset can provide insights into the health implications of the contaminants especially when the mean concentration levels of the heavy metals are compared with recommended regulatory limit concentration.
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