Neutrosophic Entropy Based Heavy Metal Contamination Indices for Impact Assessment of Sirsa River Water Quality Within County of District Baddi, India
Keywords:Neutrosophic Entropy, Deluca-Termini Entropy, Pharmaceutical Effluents, Heavy Metals Contamination
This study contributes a novel fuzzy and neutrosophic entropy-based procedure to identify the most contaminated sampling spot and to assess the impact of heavy metals concentration, before and after the amalgamation of pharmaceutical effluents treated in common effluent treatment plant. in river water samples. It is observed that the concentration of heavy metals, which were within permissible limits before amalgamation, dwindled gradually after
amalgamation, owing to the decrease in fuzzy and neutrosophic entropy values. To identify the most contaminated sampling spot, responsible for heavy metal contamination, the proposed trigonometric fuzzy and single valued neutrosophic entropy measures are fascinated for assigning weights to each monitored heavy metal concentration reading with respect to four sampling spots and thereafter coupled with the relative sub-indices of each heavy metal to construct fuzzy and neutrosophic entropy weighted heavy metal contamination indices (FHCI and NHCI). The maximum (or minimum) FHCI and NHCI score among each sampling spot is designated to the “most contaminated” or “least contaminated” sampling spot accordingly. The proposed entropy-based contamination indices are superior in providing a better insight in classifying the desired contaminated sampling spot in comparison with the existing Deluca-Termini fuzzy entropybased contamination index which may indicate uncertainty in the quality analysis of heavy metal contamination in river water samples
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