NDLI: Application of Laser-Induced, Deep UV Raman Spectroscopy and Artificial Intelligence in Real-Time Environmental Monitoring—Solutions and First Results

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Application of Laser-Induced, Deep UV Raman Spectroscopy and Artificial Intelligence in Real-Time Environmental Monitoring—Solutions and First Results

Content Provider	MDPI
Author	Simon, Brülisauer Kryss, Waldschläger Luis, Grüneis Aaron, Förderer Holger, Schüttrumpf Post, Claudia Hug, William Heyden, Niklas Schmor, Sebastian Reid, Ray Reid, Michael Bhartia, Rohit Nguyen, Quoc Amann, Florian
Copyright Year	2021
Description	Environmental monitoring of aquatic systems is the key requirement for sustainable environmental protection and future drinking water supply. The quality of water resources depends on the effectiveness of water treatment plants to reduce chemical pollutants, such as nitrates, pharmaceuticals, or microplastics. Changes in water quality can vary rapidly and must be monitored in real-time, enabling immediate action. In this study, we test the feasibility of a deep UV Raman spectrometer for the detection of nitrate/nitrite, selected pharmaceuticals and the most widespread microplastic polymers. Software utilizing artificial intelligence, such as a convolutional neural network, is trained for recognizing typical spectral patterns of individual pollutants, once processed by mathematical filters and machine learning algorithms. The results of an initial experimental study show that nitrates and nitrites can be detected and quantified. The detection of nitrates poses some challenges due to the noise-to-signal ratio and background and related noise due to water or other materials. Selected pharmaceutical substances could be detected via Raman spectroscopy, but not at concentrations in the µg/l or ng/l range. Microplastic particles are non-soluble substances and can be detected and identified, but the measurements suffer from the heterogeneous distribution of the microparticles in flow experiments.
Starting Page	3911
e-ISSN	14248220
DOI	10.3390/s21113911
Journal	Sensors
Issue Number	11
Volume Number	21
Language	English
Publisher	MDPI
Publisher Date	2021-06-05
Access Restriction	Open
Subject Keyword	Sensors Spectroscopy Environmental Monitoring Machine Learning Data Processing Real-time Water Analysis Duv Raman/fluorescence Spectroscopy
Content Type	Text
Resource Type	Article

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