期刊
ECOLOGICAL INDICATORS
卷 97, 期 -, 页码 239-246出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolind.2018.10.023
关键词
Metal pollution index; Groundwater; Hazard index; Multivariate non-linear correlation; Predictive model
Hazard index and various heavy metal pollution indices in groundwater are generally poorly correlated though all of them aim to address water quality. A semi empirical approach has been proposed for correlating Hazard Index (HI) of groundwater samples with a recently introduced heavy metal pollution index, m-HPI. m-HPI has two components, a positive index (PI) and a negative index (NI). It is possible to correlate HI with PI and NI through multivariate non-linear regression (MVNLR). Correlation performance may be improved by optimizing the weightage factor of each heavy metal. Introduction of USEPA heavy metal reference dose (RfD) in the expression for weightage factor improves the correlation still further. The newly proposed approach has been successfully validated with seven sets of water samples of different origin comprising different sets of heavy metals. The derived correlation function is generic and has global applicability as optimized m-HPI (PI and NI) data of 305 groundwater samples spread over six different locations could be well correlated with corresponding HI through a single generic correlation function employing MVNLR model. The predictive capability of MVNLR model has been demonstrated for each site. This communication has brought for the first time two poorly correlated similar narratives such as HI and heavy metal pollution index (HMPI) on the same page and provided a very useful predictive tool.
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