Articles | Volume 11, issue 11
https://doi.org/10.5194/amt-11-6351-2018
© Author(s) 2018. 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-11-6351-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Nov 2018
Research article |
| 28 Nov 2018
| 28 Nov 2018
Testing the performance of field calibration techniques for low-cost gas sensors in new deployment locations: across a county line and across Colorado
Joanna Gordon Casey
CORRESPONDING AUTHOR
Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, 80309, USA
Michael P. Hannigan
Department of Mechanical Engineering, University of Colorado at Boulder, Boulder, 80309, USA
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Cited
22 citations as recorded by crossref.
- Machine learning calibration of low-cost NO<sub>2</sub> and PM<sub>10</sub> sensors: non-linear algorithms and their impact on site transferability P. Nowack et al. 10.5194/amt-14-5637-2021
- Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring S. Vikram et al. 10.5194/amt-12-4211-2019
- Using gas-phase air quality sensors to disentangle potential sources in a Los Angeles neighborhood A. Collier-Oxandale et al. 10.1016/j.atmosenv.2020.117519
- Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring J. Silberstein et al. 10.3390/s24020519
- Physical Confounding Factors Affecting Gas Sensors Response: A Review on Effects and Compensation Strategies for Electronic Nose Applications S. Robbiani et al. 10.3390/chemosensors11100514
- State-of-the-Art Low-Cost Air Quality Sensors, Assemblies, Calibration and Evaluation for Respiration-Associated Diseases: A Systematic Review H. Tariq et al. 10.3390/atmos15040471
- Understanding the ability of low-cost MOx sensors to quantify ambient VOCs A. Collier-Oxandale et al. 10.5194/amt-12-1441-2019
- On the robustness of field calibration for smart air quality monitors S. De Vito et al. 10.1016/j.snb.2020.127869
- A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments S. De Vito et al. 10.1109/TIM.2023.3331428
- Framework for the Simulation of Sensor Networks Aimed at Evaluating In Situ Calibration Algorithms F. Delaine et al. 10.3390/s20164577
- Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age K. Okorn & M. Hannigan 10.3390/atmos12050645
- COVID-19 Lockdown in Belgrade: Impact on Air Pollution and Evaluation of a Neural Network Model for the Correction of Low-Cost Sensors’ Measurements I. Vajs et al. 10.3390/app112210563
- Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study C. Zuidema et al. 10.3390/s21124214
- Kitchen Area Air Quality Measurements in Northern Ghana: Evaluating the Performance of a Low-Cost Particulate Sensor within a Household Energy Study E. Coffey et al. 10.3390/atmos10070400
- Probabilistic Machine Learning with Low-Cost Sensor Networks for Occupational Exposure Assessment and Industrial Hygiene Decision Making A. Patton et al. 10.1093/annweh/wxab105
- Enhanced Ambient Sensing Environment—A New Method for Calibrating Low-Cost Gas Sensors H. Russell et al. 10.3390/s22197238
- Sensors and Systems for Wearable Environmental Monitoring Toward IoT-Enabled Applications: A Review M. Mamun & M. Yuce 10.1109/JSEN.2019.2919352
- In Situ Calibration Algorithms for Environmental Sensor Networks: A Review F. Delaine et al. 10.1109/JSEN.2019.2910317
- Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al. 10.1039/D2EA00165A
- A Kalman Filter Scheme for the Optimization of Low-Cost Gas Sensor Measurements I. Christakis et al. 10.3390/electronics13010025
- Applications and Limitations of Quantifying Speciated and Source-Apportioned VOCs with Metal Oxide Sensors K. Okorn & M. Hannigan 10.3390/atmos12111383
- Advantages and challenges of the implementation of a low-cost particulate matter monitoring system as a decision-making tool V. Caquilpán P. et al. 10.1007/s10661-019-7875-4
21 citations as recorded by crossref.
- Machine learning calibration of low-cost NO<sub>2</sub> and PM<sub>10</sub> sensors: non-linear algorithms and their impact on site transferability P. Nowack et al. 10.5194/amt-14-5637-2021
- Evaluating and improving the reliability of gas-phase sensor system calibrations across new locations for ambient measurements and personal exposure monitoring S. Vikram et al. 10.5194/amt-12-4211-2019
- Using gas-phase air quality sensors to disentangle potential sources in a Los Angeles neighborhood A. Collier-Oxandale et al. 10.1016/j.atmosenv.2020.117519
- Utilization of a Low-Cost Sensor Array for Mobile Methane Monitoring J. Silberstein et al. 10.3390/s24020519
- Physical Confounding Factors Affecting Gas Sensors Response: A Review on Effects and Compensation Strategies for Electronic Nose Applications S. Robbiani et al. 10.3390/chemosensors11100514
- State-of-the-Art Low-Cost Air Quality Sensors, Assemblies, Calibration and Evaluation for Respiration-Associated Diseases: A Systematic Review H. Tariq et al. 10.3390/atmos15040471
- Understanding the ability of low-cost MOx sensors to quantify ambient VOCs A. Collier-Oxandale et al. 10.5194/amt-12-1441-2019
- On the robustness of field calibration for smart air quality monitors S. De Vito et al. 10.1016/j.snb.2020.127869
- A Global Multiunit Calibration as a Method for Large-Scale IoT Particulate Matter Monitoring Systems Deployments S. De Vito et al. 10.1109/TIM.2023.3331428
- Framework for the Simulation of Sensor Networks Aimed at Evaluating In Situ Calibration Algorithms F. Delaine et al. 10.3390/s20164577
- Improving Air Pollutant Metal Oxide Sensor Quantification Practices through: An Exploration of Sensor Signal Normalization, Multi-Sensor and Universal Calibration Model Generation, and Physical Factors Such as Co-Location Duration and Sensor Age K. Okorn & M. Hannigan 10.3390/atmos12050645
- COVID-19 Lockdown in Belgrade: Impact on Air Pollution and Evaluation of a Neural Network Model for the Correction of Low-Cost Sensors’ Measurements I. Vajs et al. 10.3390/app112210563
- Deployment, Calibration, and Cross-Validation of Low-Cost Electrochemical Sensors for Carbon Monoxide, Nitrogen Oxides, and Ozone for an Epidemiological Study C. Zuidema et al. 10.3390/s21124214
- Kitchen Area Air Quality Measurements in Northern Ghana: Evaluating the Performance of a Low-Cost Particulate Sensor within a Household Energy Study E. Coffey et al. 10.3390/atmos10070400
- Probabilistic Machine Learning with Low-Cost Sensor Networks for Occupational Exposure Assessment and Industrial Hygiene Decision Making A. Patton et al. 10.1093/annweh/wxab105
- Enhanced Ambient Sensing Environment—A New Method for Calibrating Low-Cost Gas Sensors H. Russell et al. 10.3390/s22197238
- Sensors and Systems for Wearable Environmental Monitoring Toward IoT-Enabled Applications: A Review M. Mamun & M. Yuce 10.1109/JSEN.2019.2919352
- In Situ Calibration Algorithms for Environmental Sensor Networks: A Review F. Delaine et al. 10.1109/JSEN.2019.2910317
- Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al. 10.1039/D2EA00165A
- A Kalman Filter Scheme for the Optimization of Low-Cost Gas Sensor Measurements I. Christakis et al. 10.3390/electronics13010025
- Applications and Limitations of Quantifying Speciated and Source-Apportioned VOCs with Metal Oxide Sensors K. Okorn & M. Hannigan 10.3390/atmos12111383
Latest update: 19 Apr 2024
Short summary
Low-cost sensors have the potential to improve understanding of air quality in complex regions like oil and gas production basins. Regression methods have been used to quantify pollutants from sensor signals, but these methods have not been tested when sensors are moved to new sampling locations, away from model training locations. We use sensor data collected at multiple sites to test how well these field calibration methods perform when they are extended to new locations and times.
Low-cost sensors have the potential to improve understanding of air quality in complex regions...
