4.5 Article

Application of the metal pollution indices on surface waters for assessment of environmental risk: a case study for Damsa reservoir (Cappadocia, Turkiye)

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DOI: 10.1007/s13762-022-04102-1

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Heavy metal pollution index; Heavy metal evaluation index; Heavy metals; Reservoir

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Damsa reservoir is a significant water source for irrigation and recreation in Cappadocia region. Indices were used to assess heavy metal pollution in the reservoir, and the main sources of pollution were identified as natural/geogenic processes and anthropogenic inputs (agricultural activities).
Damsa reservoir is a considerable water source for the purpose of irrigation and recreation in Cappadocia region. For the assessment of heavy metals pollution, indices (heavy metal pollution index (HPI) and heavy metal evaluation index (HEI)) were used. Thus, inductively coupled plasma mass spectrometry (ICP-OES) was used for measuring the metal concentrations such as chromium (Cr), nickel (Ni), boron (B), copper (Cu), lead (Pb), cadmium (Cd), arsenic (As), zinc (Zn), manganese (Mn), selenium (Se) and antimony (Sb). These values ranged from 15.97 to 18.76 (mean 17.21) for HPI and from 0.97 to 1.44 (mean 1.21) for HEI. HPI values of measured metals were calculated as lower than 75 that is the critical value. For all samples, the values of HEI (heavy metal evaluation index) were determined as low metal pollution level. Concentration of the most metals was found within limit of WHO except boron. Additionally, concentration of arsenic was measured very close to the limit value. When evaluating HPI for critical elements, it was found to be as very poor class for arsenic (82.4) and as medium class for boron (18.98). To identify pollution origin and relationship between parameters, Pearson correlation index (PCI) and principal components analysis/factor analysis (PCA/FA) were applied to data. Natural/geogenic processes and anthropogenic (agricultural activities) inputs were determined as the main pollution sources of reservoir by the result of principal component analysis and pollution indices.

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