Chemometrics heavy metal content clustering of water samples using electrochemical data of modified carbon paste electrode

Abstract Heavy metal pollution of water samples changes the quality of water samples and these contaminations have critical effects on human health. In this study, a modification of carbon paste electrode was performed by MWCNTs and 3H-spiro[isobenzofuran-1, 6’-pyrrolo[2, 3-d]pyrimidine]-2’,3,4’,5’-tetraones (3HSIPPT). Detection limit of 0.017, 0.011, and 0.003 μmol L-1and quantification limit of 0.031, 0.04, and 0.011 μmol L-1were achieved for Hg2+, Pb2+ and Cd2+, respectively. The interference studies showed that the modified electrode is highly selective to investigate the properties in the presence of metal ions. Therefore, the fabricated sensors were effectively applied for simultaneous determination of analytes in several water samples. Additionally, principal component analysis, k-mean clustering and hierarchical clustering were applied for the classification studies using obtained metal content of target ions. The DPV and flame atomic absorption spectrometry (FAAS) results were applied for clustering of water samples. The water samples were classified into four groups using PCA. Comparison of results of classification by different methods showed that all group members determined by PCA and HC are in a good agreement with the predicted group of cases classified by k-mean clustering. Therefore, the DPV results are applicable as an efficient technique to distinguish the heavy metal pollution of water samples.