New Algorithm Created for Detecting Volatile Organic Compounds in Air

Scientists from Institut de Combustion, Aérothermique, Réactivité et Environnement (ICARE-CNRS) in Orléans, France and Chromatotec in Saint-Antoine, France recently created a new algorithm for detecting volatile organic compounds (VOCs) in ambient air. Their findings were published in the Journal of Chromatography A (1).

Volatile organic compounds (VOCs) are a type of pollutants emitted into the atmosphere from both anthropogenic and biogenic sources. These substances constitute a broad range of compounds, most of which have adverse effects on human health. Longtime exposure to areas with air pollution can lead to long-term diseases, with traces of carbonyl and aromatic compounds (formaldehyde and benzene) being traced to some incidents of cancers and pulmonary issues (2,3).

There are multiple techniques commonly used for detecting and monitoring VOCs, such as portable sensors, proton transfer reaction mass spectrometry (PTR-MS), and thermal desorption gas chromatography (TD-GC). The latter system is used both off- and online with flame ionization detectors (FID) and mass spectrometers (MS). Large numbers of molecules are detected per chromatogram, meaning that data generated by these monitoring techniques are typically checked and reprocessed manually. However, this process can be very time-consuming, increasing the risk of human error. As such, changes must be made to provide results as quickly as possible (1).

Read More: Identifying Volatile Organic Compounds (VOCs) Originating from Breath with TD-GC–MS

For this study, the scientists tested the performances of an online thermal desorption gas chromatography (TD-GC) system with dual detection FID and MS. 60 VOCs (alkanes, aromatics, oxygenated, and halogenated) were put through the detectors, with their method detection limits (MDL), linearities, and accuracies being calculated. The MDLs and accuracies ranged from 0.006 to 0.618 ppbv and from 77% to 100% for FID, and from 0.018 to 0.760 ppbv and from 80% to 100% for MS. Both detectors not only showed good complementarity, but also allowed for two programs to be developed for facilitating data analysis (1).

These algorithms were designed to autonomously select optimal results between FID and MS detectors, in hopes of saving time during data analysis. They were later evaluated for outdoor and indoor measurement conditions, since robustness and reproducibility of data analysis are often major challenges in the field. The first version of the algorithm, while sufficient at analyzing data at ppbv levels, was limited under 0.5 ppbv. With the second version, the detectors’ method detection limits were noted, with the low concentration levels being typically encountered under field conditions. This algorithm is fed by performance studies of the calibrated compounds, enhancing its reliability. Version 2 of the algorithm is a significant improvement regarding automatic data processing, especially for field campaigns where more than 1000 chromatograms are acquired per month (1).

While this new version of the algorithm, there is more work to be done to improve this process. Extension of this work will focus on automatic evaluation of the uncertainties associated with sections of the algorithm. Furthermore, various challenges exist when measuring VOCs under field conditions, especially data processing time. Future algorithms of this type that exploit the complementarity of multi-analytical methods will be useful in other dual-detector systems, or for campaigns deploying different instruments where they are sufficiently calibrated (1).

References

(1) Bachelier, F.; Mascles, M.; McGillen, M. R.; Amiet, J-P.; Grosselin, B.; Bazhin, D.; Daële, V. Development, Optimization and Validation of Automated Volatile Organic Compound Data Analysis Using an On-Line Thermal Desorption Gas Chromatograph with Dual Detection and Application to Measurements in Ambient Air. J. Chromatogr. A 2024, 1735, 465327. DOI: 10.1016/j.chroma.2024.465327

(2) Fortin, T. J.; Howard, B. J.; Parrish, D. D.; et al. Temporal Changes in U.S. Benzene Emissions Inferred from Atmospheric Measurements. Environ. Sci. Technol. 2005, 39 (6), 1403–1408. DOI: 10.1021/es049316n

(3) Kim, K-H.; Jahan, S. A.; Lee, J-T. Exposure to Formaldehyde and Its Potential Human Health Hazards. J. Environ. Sci. Health Part C 2011, 29 (4), 277–299. DOI: 10.1080/10590501.2011.629972