Soil Metals Analysis Using Laser‐Induced Breakdown Spectroscopy (LIBS)

Abstract

Laser‐induced breakdown spectroscopy (LIBS) is an elemental analysis technique that is based on the measurement of atomic emissions generated on a sample surface by a laser‐induced microplasma. Although often recognized in the literature as a well‐established analytical technique, LIBS remains untested relative to the quantitative analysis of elements in chemically complex matrices, such as soils. The objective of this study was to evaluate the capabilities of LIBS relative to the elemental characterization of surface soils. Approximately 65 surface soil samples from the Pond Creek watershed in east Tennessee were collected and subjected to total dissolution and elemental analysis by inductively coupled argon plasma‐optical emission spectroscopy (ICP–OES). The samples were analyzed by LIBS using a Nd:YAG laser at 532 nm, with a beam energy of 25 mJ per pulse, a pulse width of 5 ns, and a repetition rate of 10 Hz. The wavelength range for the LIBS spectra collection was 200 to 600 nm, with a resolution of 0.03 nm. Elemental spectral lines were identified through the analysis of analytical reagent‐grade chemicals and the NIST and Kurucz spectral databases. The elements that dominated the LIBS spectra were Al, Ca, Fe, and Mg. In addition, emission lines for Ti, Ba, Na, Cu, and Mn were isolated. The emission lines of Cr, Ni, and Zn, which were >100 mg kg−1 in numerous soil samples, were not detected. Further, spectral emission lines for P and K are >600 nm, eliminating them from LIBS analysis. The integrated peak areas of interference‐free elemental emission lines were determined, then normalized to the area of the 288.16 nm Si(I) emission (internal standard) to reduce the variability between replicate analyses. The normalized spectral areas, coupled with linear regression (standard curves for single wavelength response) and multivariate techniques (chemometrics and multiple wavelengths), were used to predict ICP–OES elemental data. In general, the quantitative capabilities of LIBS proved disappointing. Detection and quantitation were generally restricted to those elements with concentrations > 0.5 g kg−1 The correlation between LIBS response and elemental content was poor (r < 0.98). Further, the relative errors of prediction for the LIBS‐detected elements were less than acceptable for an analytical technique (<20%), ranging from ∼20 to ∼40% using linear regression analysis, and from 18 to 48% using partial least squares analysis. Based on these findings, the analytical capability of the LIBS method for soil metals analysis should be considered questionable.

Nuclear Methodology for Non-Destructive Multi-Elemental Analysis of Large Volumes of Soil

“…LIBS is a well-established atomic-emission technique extensively applied for surface analyses in research and industry (Balzer et al, 2005;Essington et al, 2009;Merdes et al, 2007). It involves focusing a pulsed laser-beam ~50 μm diameter on a sample and ablating a small amount, ~10 -9 cm 3 , of the material (Martin et al, 2010).…”

Artificial neural network for on-site quantitative analysis of soils using laser induced breakdown spectroscopy

“…Al, Si) and some other with a very high number of spectral lines (e.g. Fe, Ti, Mn, Ca) rising up the risk of spectral interference [12]. Consequently, quantitative LIBS remains very challenging and specific studies should be conducted either to take into account the matrix effect through advanced data processing in the case of the approach with calibration or to discuss the condi tions of stoichiometry for applying the calibration free algorithm.…”

“…Later, Sirven et al [15] used partial least square regression (PLS) to quantify chromium in artificially prepared soil samples and obtained a good improvement of prediction of concen trations compared to univariate calibration method. But at the opposite, Essington et al [12] applied PLS to LIBS and ICP AES data from natural soils originating from East Tennessee and obtained relative errors of prediction not smaller than the one provided by univariate approach. They also noticed that the analytically viable methods of analysis are de fined by an average relative error of prediction below 20%.…”

Multivariate Analysis of Laser-Induced Breakdown Spectroscopy Spectra of Soil Samples

“…A method that is fast, accurate, and cost effective is needed for estimating heavy metal concentration in soils. Conventional atomic spectroscopic techniques have acceptable analytical performance, but their sample preparation is time consuming and requires the use of hazardous chemicals (Hussain et al, 2007;Essington et al, 2009). Laser-induced breakdown spectroscopy (LIBS) is a fast total-elemental analytical technique that has potential advantages over the conventional analytical techniques because of a simple and compact experimental setup, less sample preparation, less destructive, and can be used in remote in-situ analysis in hostile environments and hazardous or inaccessible targets (Miziolek et al, 2006;Hussain et al, 2007;Martin et al, 2010).…”

“…However, for spectra obtained from soil samples, the previous method is not practical because soil is a chemically complex matrix containing a host of other elements. Essington et al (2009) reported that soil spectra were dominated by peaks of Al, Ca, Mg, and Fe, and some of which had more than a hundred peaks. The existence of these soil elements can interfere and overshadow most of the trace elements that might be of interest and make it hard to identify all the useful peaks for the specific element.…”