H-Point standard addition method for simultaneous spectrophotometric determination of toxic metals and pesticides in micellar media

Abstract

India, being a developing nation, has undergone rapid industrialization in the last few decades. With the enormous growth and expansion of technology, a serious problem of environmental pollution has cropped up, which has now become a major threat for vegetation and animal life. In various forms, cruel hands of pollution are throttling the living humanism. Water, is being contaminated more and more by the toxic metals and pesticides and is responsible for water pollution. Thus pollution is an unavoidable consequence of industrialization and the ultimate cause of the poorer global environmental quality. Although some of the metals are essential nutrients for plants and animal metabolism (glucose metabolism, amino acid metabolism), yet accumulated at high levels, these can cause serious disorders and diseases (nausea, skin ulceration, lung cancer etc.) and they ultimately become lethal. Thus metals like nickel, iron, manganese and mercury pose potential danger so, it is necessary to develop a rapid and accurate analytical method for their determination. Quantitative analysis often involves the spectrophotometric resolution of mixtures of two components with partly or completely overlapping spectra the greater the extent of overlapping the more difficult the resolution is rendered. Not surprisingly, this topic has been the subject of a number of chemometric studies originally intended for the resolution of binary mixtures and later extended to three or more components. The multi-component linear additive model is frequently used in resolving mixtures. Its application requires assuming the measured response to be made up of the sole contributions of the known components of the sample. This in turn requires knowledge not only of the analytes of interest, but also of all interferents potentially present. Least-squares fitting techniques are probably the most commonly employed to estimate the concentration of several components in a mixture; however the reliability of the results.