A new indexing approach for evaluating heavy metal contamination in groundwater

• Published in: Chemosphere (Oxford) 2020-04, Vol.245, p.125598, Article 125598
• Main Authors: Rajkumar, Herojeet, Naik, Pradeep K., Rishi, Madhuri S.
• Format: Article
• Language: English
• Subjects: Chemometric techniques; Cluster Analysis; Environmental Monitoring - methods; Environmental Pollution - analysis; Groundwater; Groundwater - chemistry; HCI; Heavy metals; Humans; India; Metals, Heavy - analysis; Pollution indices; Risk Assessment; Water Pollutants, Chemical - analysis; Water Quality - standards
• ISSN: 0045-6535; 1879-1298
• DOI: 10.1016/j.chemosphere.2019.125598

Three indexing methods, namely heavy metal pollution index (HPI), contamination index (Cd) and heavy metal evaluation index (HEI), are commonly used for heavy metal evaluation in groundwater. These methods have several limitations. In HPI, 14 out of 15 groundwater samples collected in the study area of Nalagarh valley, Himachal Pradesh, India qualify for drinking purposes with their values varying between 10.73 and 107.50 (critical limit = 100), while in Cd, the same number of samples (>90%) are rejected as their values (Cd = 1.31–37.87) exceed the critical limit of 3. HEI varies from 10.31 to 46.87 with a mean of 26.06, but since it does not have a defined critical limit, quality assessment depends on worker’s discretion. It thus becomes very confusing as to which indexing method to use. To overcome this dilemma, a very simple indexing method called ‘heavy metal contamination index (HCI)’ has been developed on the basis of assigning weight to each heavy metal parameter. A new classification system with six distinct water classes of different uses too has been proposed considering the regulatory limits, human health risk and toxicity of the violator parameters. Regression analysis confirms that HCI has larger number of significantly correlated key parameters compared to the other three indices. Chemometric techniques confirm that Cr, Cu, Fe, Mn and Zn are derived from lithogenic inputs and As, Cd, Ni and Pb from anthropogenic sources. HCI when integrated with Cluster Analysis gives the best possible results in identifying factors that influence the various water classes. •Evaluated conventionally used indices: heavy metal pollution index, contamination index and heavy metal evaluation index.•Developed of a new indexing approach, heavy metal contamination index (HCI), with a set of six distinct water classes.•Assigned weightage to heavy metal parameters through Delphi’s method for computing HCI.•Applied chemometric techniques for distinguishing various sources of heavy metal contamination.•Integrated HCI with cluster analysis for verifying possible factors and extent of groundwater contamination.