LIBS Sensing for In-Situ Iron Detection and Quantification in Wastewater Outfall

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Abstract
Iron measurement in water is important to ensure its quality. Although iron is essential for good health, when its level in water exceeds the permitted limit, it can cause health- and environmental-related issues. In this study, a spectroscopic methodology based on laser-induced breakdown spectroscopy (LIBS) has been developed for in-situ detection and quantification of iron in water. Wastewater from the foundation of a historic building at the National Energy Technology Laboratory (NETL) Morgantown site was collected for ten continual days and analyzed with the LIBS benchtop system and NETL’s LIBS probe. Spectral signatures of iron in the LIBS spectra were identified which demonstrated the significant presence of iron in the test samples. Machine learning tools, principal component analysis (PCA) and linear discriminant analysis (LDA), were used to distinguish the ten liquid samples. For quantitative study, univariate and multivariate analyses were performed. While two strong emission lines of iron, Fe I 371.9 nm and Fe I 373nm, were used to develop the calibration curve for univariate analysis, whole spectra in the selected wavelength range were utilized to plot the partial least square regression (PLS-R) curve. These calibration curves were then used to estimate the iron content in water samples, and the estimated values were compared to inductively coupled plasma-mass spectrometry (ICP-MS) measurements. The relative difference was found to be less than 15%, which shows that the iron content in liquid can be reliably detected and quantified by the LIBS-based spectroscopic technique.

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