Abstract: Contaminated soil with heavy metals is considered as one of the most critical environmental issues. Regarding heavy metals analysis, traditional analytical approaches such as atomic absorption spectrometry, inductively coupled plasma atomic emission spectroscopy, ICP-optical emission spectroscopy and ICP-mass spectroscopy have been widely used. Due to the complexity of those approaches, in the recent decade, the method of Laser-Induced Breakdown Spectroscopy has been more investigated with the relevant simplification concerning qualitative and quantitative analysis. However, for soil investigation, the matrix effect owing to the interaction of heavy metals and soil particles resulted in physical and chemical altering makes it more complicated in comparison with using LIBS approach in ordinary applications. In this study, the calibration curve method was investigated regarding the detection of heavy metals. In order to reduce matrix effect, standard normal variate (SNV) was conducted. Also, the value of coefficient of determination (R2), relative standard deviation (RSD), and Root Mean Squared Error of prediction (RMSE) concerning model efficiency and prediction accuracy were studied. Results showed that the SNV normalization increase the analytical performance of LIBS approach in some elements.
About this group: LIEC aims to understand the functioning of continental environments strongly impacted by human activity, in order to contribute to their rehabilitation. In this purpose, LIEC implement an interdisciplinary research, allying the concepts and methods of environmental mineralogy, soil science, microbial ecology, colloidal physiochemistry, ecotoxicology, and functional ecology.
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