Accurate method based on data filtering for quantitative multi-element analysis of soils using CF-LIBS

Abstract

Abstract To obtain more stable spectral data for accurate quantitative analysis of multi-element, especially for the large-area in-situ elements detection of soils, we propose a method for a multi-element quantitative analysis of soils using calibration-free laser-induced breakdown spectroscopy (CF-LIBS) based on data filtering. In this study, we analyze a standard soil sample doped with two heavy metal elements, Cu and Cd, with a specific focus on the line of Cu I 324.75 nm for filtering the experimental data of multiple sample sets. Pre- and post- data filtering, the relative standard deviation for Cu decreased from 30% to 10%, The limits of detection (LOD) values for Cu and Cd decreased by 5% and 4%, respectively. Through CF-LIBS, a quantitative analysis was conducted to determine the relative content of elements in soils. Using Cu as a reference, the concentration of Cd was accurately calculated. The results show that post- data filtering, the average relative error of the Cd decreases from 11% to 5%, indicating the effectiveness of data filtering in improving the accuracy of quantitative analysis. Moreover, the content of Si, Fe and other elements can be accurately calculated using this method. To further correct the calculation, the results for Cd was used to provide a more precise calculation. This approach is of great importance for the large-area in-situ heavy metals and trace elements detection in soil, as well as for rapid and accurate quantitative analysis.