Process Gas Chromatography

Villalobos, Richard

doi:10.1021/ac60361a778

Cited by 14 publications

(3 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Process analyzers, such as gas chromatographs with simple detectors [73][74][75], TOCanalyzers, spectroscopic probes and many others are very common in the process envi-ronment and have already been implemented successfully in (petro-)chemical plants or wastewater treatment plants for many years [76]. These techniques (e.g., GC, HPLC and IC systems) mainly use mass spectrometric detection which does not allow truly continuous monitoring.…”

Section: Wastewater Treatment and Monitoringmentioning

confidence: 99%

Possibilities of Real Time Monitoring of Micropollutants in Wastewater Using Laser-Induced Raman & Fluorescence Spectroscopy (LIRFS) and Artificial Intelligence (AI)

Post

Heyden

Reinartz

et al. 2022

Sensors

View full text Add to dashboard Cite

The entire water cycle is contaminated with largely undetected micropollutants, thus jeopardizing wastewater treatment. Currently, monitoring methods that are used by wastewater treatment plants (WWTP) are not able to detect these micropollutants, causing negative effects on aquatic ecosystems and human health. In our case study, we took collective samples around different treatment stages (aeration tank, membrane bioreactor, ozonation) of a WWTP and analyzed them via Deep-UV laser-induced Raman and fluorescence spectroscopy (LIRFS) in combination with a CNN-based AI support. This process allowed us to perform the spectra recognition of selected micropollutants and thus analyze their reliability. The results indicated that the combination of sensitive fluorescence measurements with very specific Raman measurements, supplemented with an artificial intelligence, lead to a high information gain for utilizing it as a monitoring purpose. Laser-induced Raman spectroscopy reaches detections limits of alert pharmaceuticals (carbamazepine, naproxen, tryptophan) in the range of a few µg/L; naproxen is detectable down to 1 × 10−4 mg/g. Furthermore, the monitoring of nitrate after biological treatment using Raman measurements and AI support showed a reliable assignment rate of over 95%. Applying the fluorescence technique seems to be a promising method in observing DOC changes in wastewater, leading to a correlation coefficient of R2 = 0.74 for all samples throughout the purification processes. The results also showed the influence of different extraction points in a cleaning stage; therefore, it would not be sensible to investigate them separately. Nevertheless, the interpretation suffers when many substances interact with one another and influence their optical behavior. In conclusion, the results that are presented in our paper elucidate the use of LIRFS in combination with AI support for online monitoring.

show abstract

Section: Wastewater Treatment and Monitoringmentioning

confidence: 99%

Possibilities of Real Time Monitoring of Micropollutants in Wastewater Using Laser-Induced Raman & Fluorescence Spectroscopy (LIRFS) and Artificial Intelligence (AI)

Post

Heyden

Reinartz

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…A useful definition of a process analyzer is, "an environ-mentally suitable automatic device that continuously or periodically measures one or more chemical parameters in a process stream and presents the results in a usable form." This definition is exemplified in the infrared analyzer article cited above (3) and in an older article describing process gas chromatography (4). A process analyzer sampling system can be characterized as, "a device or combination of devices which will transfer a sample from a process stream to a process analyzer in such a way as to minimize maintenance and to preserve or enhance the analytical information contained in the sample.…”

Section: Process Analyzer Sampling Systemsmentioning

confidence: 99%