Articles | Volume 16, issue 13
https://doi.org/10.5194/amt-16-3391-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-16-3391-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Jul 2023
Research article |
| 05 Jul 2023
| 05 Jul 2023
Characterising the methane gas and environmental response of the Figaro Taguchi Gas Sensor (TGS) 2611-E00
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
Olivier Laurent
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
Luc Lienhardt
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
Grégoire Broquet
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
Rodrigo Rivera Martinez
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
Elisa Allegrini
SUEZ Smart Solutions, 15-27 Rue de Port, 92000 Nanterre, France
Philippe Ciais
Laboratoire des Sciences du Climat et de l'Environnement
(CEA-CNRS-UVSQ), Institut Pierre-Simon Laplace, Université Paris-Saclay, Site de l'Orme des Merisiers, 91191 Gif-sur-Yvette, France
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Cited
12 citations as recorded by crossref.
- Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning E. Kiplimo et al. 10.3390/atmos15111313
- Temperature Modulation of MOS Sensors for Enhanced Detection of Volatile Organic Compounds A. Rescalli et al. 10.3390/chemosensors11090501
- Quantifying Methane Emission Rates Using Downwind Measurements S. Riddick 10.3390/encyclopedia5020057
- Design and evaluation of a low-cost sensor node for near-background methane measurement D. Furuta et al. 10.5194/amt-17-2103-2024
- Using metal oxide gas sensors to estimate the emission rates and locations of methane leaks in an industrial site: assessment with controlled methane releases R. Rivera-Martinez et al. 10.5194/amt-17-4257-2024
- Technical note: Pondi – a low-cost logger for long-term monitoring of methane, carbon dioxide, and nitrous oxide in aquatic and terrestrial systems M. Malerba et al. 10.5194/bg-22-5051-2025
- Characterizing the Effect of Simultaneous Enhancements of Reducing Gas Species on Figaro Taguchi Gas Sensor Resistance Response A. Shah et al. 10.1021/acsomega.4c06397
- The Silent Language: A Review of Mathematics in the Realm of Gas Sensing G. Hingangavkar 10.1007/s11220-025-00654-x
- Determining methane mole fraction at a landfill site using the Figaro Taguchi gas sensor 2611-C00 and wind direction measurements A. Shah et al. 10.1039/D3EA00138E
- Design, Build, and Initial Testing of a Portable Methane Measurement Platform S. Riddick et al. 10.3390/s25071954
- Characterising changes in the methane response of a semiconductor-based metal oxide sensor over time A. Shah et al. 10.1039/D5EA00046G
- Electronic Nose for Improved Environmental Methane Monitoring G. Domènech-Gil et al. 10.1021/acs.est.3c06945
11 citations as recorded by crossref.
- Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning E. Kiplimo et al. 10.3390/atmos15111313
- Temperature Modulation of MOS Sensors for Enhanced Detection of Volatile Organic Compounds A. Rescalli et al. 10.3390/chemosensors11090501
- Quantifying Methane Emission Rates Using Downwind Measurements S. Riddick 10.3390/encyclopedia5020057
- Design and evaluation of a low-cost sensor node for near-background methane measurement D. Furuta et al. 10.5194/amt-17-2103-2024
- Using metal oxide gas sensors to estimate the emission rates and locations of methane leaks in an industrial site: assessment with controlled methane releases R. Rivera-Martinez et al. 10.5194/amt-17-4257-2024
- Technical note: Pondi – a low-cost logger for long-term monitoring of methane, carbon dioxide, and nitrous oxide in aquatic and terrestrial systems M. Malerba et al. 10.5194/bg-22-5051-2025
- Characterizing the Effect of Simultaneous Enhancements of Reducing Gas Species on Figaro Taguchi Gas Sensor Resistance Response A. Shah et al. 10.1021/acsomega.4c06397
- The Silent Language: A Review of Mathematics in the Realm of Gas Sensing G. Hingangavkar 10.1007/s11220-025-00654-x
- Determining methane mole fraction at a landfill site using the Figaro Taguchi gas sensor 2611-C00 and wind direction measurements A. Shah et al. 10.1039/D3EA00138E
- Design, Build, and Initial Testing of a Portable Methane Measurement Platform S. Riddick et al. 10.3390/s25071954
- Characterising changes in the methane response of a semiconductor-based metal oxide sensor over time A. Shah et al. 10.1039/D5EA00046G
1 citations as recorded by crossref.
Latest update: 26 Oct 2025
Short summary
As methane (CH4) contributes to global warming, more CH4 measurements are required to better characterise source emissions. Hence, we tested a cheap CH4 sensor for 338 d of landfill sampling. We derived an excellent CH4 response model in a stable environment. However, different types of air with the same CH4 level had diverse sensor responses. We characterised temperature and water vapour response but could not replicate field sampling. Thus, other species may cause sensor interactions.
As methane (CH4) contributes to global warming, more CH4 measurements are required to better...
