A Novel Approach for Indexing Heavy Metals Pollution to Assess Groundwater Quality for Drinking Purposes

Elsiddig Eldaw, Tao Huang, Basheer Elubid, Adam Khalifa Mahamed and Yahaya Mahama
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Elsiddig Eldaw: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Tao Huang: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Basheer Elubid: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Adam Khalifa Mahamed: Faculty of Geoscience and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
Yahaya Mahama: School of Transportation and Logistics Engineering, Southwest Jiaotong University, Chengdu 611756, China

IJERPH, 2020, vol. 17, issue 4, 1-16

Abstract: The present study proposes a new approach for indexing heavy metals ions to examine groundwater quality in North Kurdufan Province, Sudan. The new approach is developed based on the most frequently used methods for indexing heavy metals pollution in water. It is created in order to avoid the weaknesses of the current indexing systems. As per the new indexing approach, heavy metal contamination in water samples is evaluated by two types of indices: the negative evaluation index (NEI) and positive evaluation index (PEI). The water worthiness is assessed based on a pair of indices, NEI and PEI. Water quality increases with the decrease of PEI and NEI values. NEI indicates the contribution of heavy metals with a concentration not exceeding the highest desirable limit ( I i ) in the water sample, while vice versa regarding the PEI. If all heavy metals concentrations in the water sample do not exceed I i , the sum of NEI should be less than zero, but not less than −100, implying that the sum of PEI will be zero. When all heavy metals concentration exceeds I i , the sum of NEI should be equal to zero, and PEI will be greater than zero. The results of the newly proposed approach have been discussed and compared with the existing indexing methods as regards to the best and worst samples. The spatial distribution of NEI and PEI are in complete agreement with the metals spatial distribution. The comparison result showed that the new index is robust, with fair calculations, and gives the best classification of groundwater quality.

Keywords: groundwater quality; heavy metals contamination; MHEI; NEI; PEI; SSMO (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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