Faculty of Engineering

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The Faculty of Engineering at Stellenbosch University is one of South Africa's major producers of top quality engineers. Established in 1944, it currently has five Engineering Departments.

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Browsing Faculty of Engineering by browse.metadata.advisor "Archer, Edward"

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    Investigating the potential of near-infrared spectroscopy for the detection of low-concentration CECs in water
    (Stellenbosch : Stellenbosch University, 2023-03) Lourens, Cordilia; Burger, Andries Jacobus; Archer, Edward; Swartz, CD; Stellenbosch University. Faculty of Engineering. Dept. of Chemical Engineering.
    ENGLISH ABSTRACT: The presence of so-called contaminants of emerging concern (CECs) in water is a significant issue in many countries. Their low concentrations, complex matrices, and wide range of compositions (with varying physical-chemical properties) pose many challenges to their rapid identification and quantification. Consequently, there is a need for the development of reliable, fast, and low-cost monitoring techniques that warn of any irregular changes in CEC-related water quality, which can then prompt detailed analysis by standard methods. Near-infrared (NIR) spectroscopy, in conjunction with chemometrics, is one such technique that could potentially be utilised for near-real-time monitoring and detection of selected CECs. Therefore, this study endeavoured to develop a better understanding of the potential of NIR spectroscopy for detection of changes in the water spectrum that may indicate a CEC-related deterioration in water quality. The applicability of the method was considered by performing multivariate analysis on the NIR spectral data of deionised water spiked with surrogate CECs typically associated with anthropogenic pollution. Standard deviations of less than 0.16% and less than 0.71%, during the repeatability and reproducibility tests, respectively, suggested a high precision of the NIR method. The ratio of the standard deviation over the mean were less than 0.2% for the repeatability tests, and less than 1.16% for the reproducibility tests. This allowed for the development of a CEC classification model. A pre-feasibility study was firstly conducted, considering the following five CECs at concentrations varying between 0.001 mg/L and 1000 mg/L: carbamazepine, caffeine, efavirenz, sulfamethoxazole and trimethoprim. Positive pre-feasibility results – indicating that NIR spectroscopy indeed has potential as a rapid screening method – prompted further detailed experiments with three typical surrogate CECs, viz acetaminophen, benzotriazole and caffeine. Exploratory data analysis using principal component analysis (PCA) revealed that two spectral regions, 1300–1600 nm and 1600–2200 nm, where the appropriate wavelength regions in which to perform the investigation. The PCA score plots of the surrogate CECs showed good separation between the NIR spectra of the test chemicals and the deionised water. However, for acetaminophen and benzotriazole good separation was only possible at high concentration ranges (10–1000 mg/L) – notably higher than typical concentrations at which they occur in polluted surface water. On the other hand, caffeine samples showed separation at all the tested concentrations (0.00001–1000 mg/L), and thereby suggesting the potential application of NIR spectroscopy for the detection of caffeine at typical concentrations found in the environment. Partial least squares discriminant analysis (PLS-DA) showed that it was possible to differentiate between acetaminophen and the deionised water at a minimum concentration of 10 mg/L using the PLS-DA model with a 92.6% classification accuracy. For caffeine, differentiation was possible at a minimum concentration of 0.01 mg/L, with model classification accuracies of 87%. These results corroborated the results from the exploratory analysis with PCA. Differentiation between benzotriazole and the deionised water using PLSDA was successful to a minimum concentration of 0.1 mg/L, coinciding with findings from previous studies. The results of some preliminary evaluation tests performed on river water samples were unsatisfactory. As expected, it showed that NIR measurements in water containing salts and organics (potentially also several CECs) would be influenced adversely by such dissolved components, thereby complicating potential realtime application of these methods. Further in-depth research is therefore required, where a wider variety of matrices (such as surface water, groundwater, and wastewater), are included in the experimental design. NIR spectroscopy combined with multivariate data analysis has shown promising potential for detecting contaminants of emerging concern at mg/L and even high µg/L levels. However, implementation of the method as a (near)-real time early warning system for detecting CECs at environmental concentrations (at ng/L levels) is not yet a practical possibility.