Articles | Volume 15, issue 17
https://doi.org/10.5194/amt-15-5117-2022
© Author(s) 2022. 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-15-5117-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Characterization of inexpensive metal oxide sensor performance for trace methane detection
Daniel Furuta
Department of Bioproducts and Biosystems Engineering, University of Minnesota, 1390 Eckles Ave., St. Paul, MN 55108, USA
Tofigh Sayahi
Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA
Jinsheng Li
Department of Bioproducts and Biosystems Engineering, University of Minnesota, 1390 Eckles Ave., St. Paul, MN 55108, USA
Bruce Wilson
Department of Bioproducts and Biosystems Engineering, University of Minnesota, 1390 Eckles Ave., St. Paul, MN 55108, USA
Albert A. Presto
Department of Mechanical Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA
Department of Bioproducts and Biosystems Engineering, University of Minnesota, 1390 Eckles Ave., St. Paul, MN 55108, USA
Department of Mechanical and Aerospace Engineering, University of Miami, 1251 Memorial Drive, Coral Gables, FL 33146, USA
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Cited
14 citations as recorded by crossref.
- Optimizing Point-in-Space Continuous Monitoring System Sensor Placement on Oil and Gas Sites M. Jia et al. 10.1021/acssusresmgt.4c00333
- Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning E. Kiplimo et al. 10.3390/atmos15111313
- Characterising the methane gas and environmental response of the Figaro Taguchi Gas Sensor (TGS) 2611-E00 A. Shah et al. 10.5194/amt-16-3391-2023
- 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
- Low-cost fixed sensor deployments for leak detection in North American upstream oil and gas: Operational analysis and discussion of a prototypical program T. Barchyn et al. 10.1525/elementa.2023.00045
- Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data K. Barkjohn et al. 10.1021/acsestair.4c00125
- Application of Machine Learning for Calibrating Gas Sensors for Methane Emissions Monitoring B. Andrews et al. 10.3390/s23249898
- 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 and evaluation of a low-cost sensor node for near-background methane measurement D. Furuta et al. 10.5194/amt-17-2103-2024
- Quantifying Methane Emission Rates Using Downwind Measurements S. Riddick 10.3390/encyclopedia5020057
- Nanotechnology and E-Sensing for Food Chain Quality and Safety E. Poeta et al. 10.3390/s23208429
- Design, Build, and Initial Testing of a Portable Methane Measurement Platform S. Riddick et al. 10.3390/s25071954
- Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring J. Silberstein et al. 10.3390/s24020519
- Characterization of inexpensive metal oxide sensor performance for trace methane detection D. Furuta et al. 10.5194/amt-15-5117-2022
13 citations as recorded by crossref.
- Optimizing Point-in-Space Continuous Monitoring System Sensor Placement on Oil and Gas Sites M. Jia et al. 10.1021/acssusresmgt.4c00333
- Addressing Low-Cost Methane Sensor Calibration Shortcomings with Machine Learning E. Kiplimo et al. 10.3390/atmos15111313
- Characterising the methane gas and environmental response of the Figaro Taguchi Gas Sensor (TGS) 2611-E00 A. Shah et al. 10.5194/amt-16-3391-2023
- 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
- Low-cost fixed sensor deployments for leak detection in North American upstream oil and gas: Operational analysis and discussion of a prototypical program T. Barchyn et al. 10.1525/elementa.2023.00045
- Air Quality Sensor Experts Convene: Current Quality Assurance Considerations for Credible Data K. Barkjohn et al. 10.1021/acsestair.4c00125
- Application of Machine Learning for Calibrating Gas Sensors for Methane Emissions Monitoring B. Andrews et al. 10.3390/s23249898
- 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 and evaluation of a low-cost sensor node for near-background methane measurement D. Furuta et al. 10.5194/amt-17-2103-2024
- Quantifying Methane Emission Rates Using Downwind Measurements S. Riddick 10.3390/encyclopedia5020057
- Nanotechnology and E-Sensing for Food Chain Quality and Safety E. Poeta et al. 10.3390/s23208429
- Design, Build, and Initial Testing of a Portable Methane Measurement Platform S. Riddick et al. 10.3390/s25071954
- Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring J. Silberstein et al. 10.3390/s24020519
1 citations as recorded by crossref.
Latest update: 08 May 2025
Short summary
Methane is a major greenhouse gas and contributor to climate change with various human-caused and natural sources. Currently, atmospheric methane is expensive to sense. We investigate repurposing cheap methane safety sensors for atmospheric sensing, finding several promising sensors and identifying some of the challenges in this approach. This work will help in developing inexpensive sensor networks for methane monitoring, which will aid in reducing methane leaks and emissions.
Methane is a major greenhouse gas and contributor to climate change with various human-caused...