Abstract
Heavy metals have been widely applied in industry, agriculture, and other fields because of their outstanding physics and chemistry properties. They are non-degradable even at low concentrations, causing irreversible harm to the human and other organisms. Therefore, it is of great significance to develop high accuracy and sensitivity as well as stable techniques for their detection. Raman scattering spectroscopy and atomic absorption spectrophotometer (AAS) were used parallelly to detect heavy metal ions such as Hg, Cd, and Pb of different concentrations in fish samples. The concentration of the heavy metals is varied from 5 ppb to 5 ppm. Despite the satisfactory recoveries of AAS, their drawbacks are imperative for an alternative technique. In Raman scattering spectroscopy, the intensities and areas of the characteristic peaks are increased with increasing the concentration of the heavy metals. For Hg concentration ≥ 1 ppm, a slight shift is observed in the peak position. The obtained values of peak intensity and peak area are modeled according to Elvoich, Pseudo-first order, Pseudo-second order, and asymptotic1 exponential model. The best modeling was obtained using the Elovich model followed by the asymptotic1 exponential model. The introduced Raman spectroscopy-based approach for on-site detection of trace heavy metal pollution in fish samples is rapid, low-cost, and simple to implement, increasing its visibility in food safety and industrial applications.
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