Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7221-2021
© Author(s) 2021. 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-14-7221-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 Nov 2021
Research article |
| 17 Nov 2021
| 17 Nov 2021
Unravelling a black box: an open-source methodology for the field calibration of small air quality sensors
Seán Schmitz
CORRESPONDING AUTHOR
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Sherry Towers
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Guillermo Villena
Physikalische und Theoretische
Chemie/FK4, Bergische Universität Wuppertal, Gaussstrasse 20, 42119 Wuppertal, Germany
Alexandre Caseiro
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Robert Wegener
Forschungszentrum Jülich GmbH, Institute of Energy and Climate
Research, IEK8: Troposphere, 52425 Jülich, Germany
Dieter Klemp
Forschungszentrum Jülich GmbH, Institute of Energy and Climate
Research, IEK8: Troposphere, 52425 Jülich, Germany
Ines Langer
Institut für Meteorologie, Freie Universität Berlin,
Carl-Heinrich-Becker Weg 6–10, 12165 Berlin, Germany
Fred Meier
Chair of Climatology, Institute of Ecology, Technische Universität Berlin, Rothenburgstraße 12, 12165 Berlin, Germany
Erika von Schneidemesser
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
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Cited
21 citations as recorded by crossref.
- Time-generative AI-enabled temporal fusion transformer model for efficient air pollution sensor calibration in IIoT edge environments S. Henna et al. https://doi.org/10.3934/environsci.2025024
- Convolutional Neural Networks on Correlation between GC−MS Molecular Data and QCM Gas-Sensing Data T. Oon-pitipongsa et al. https://doi.org/10.1021/acssensors.5c03066
- Low-cost system application for policy assessment: a case study from Berlin A. Caseiro et al. https://doi.org/10.1088/2752-5309/ad56bb
- QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation S. Diez et al. https://doi.org/10.1038/s41597-024-03767-2
- Calibration and validation-based assessment of low-cost air quality sensors J. Dong et al. https://doi.org/10.1016/j.scitotenv.2025.179364
- Harness low-cost sensors for the targeted assessment of policy S. Schmitz & E. von Schneidemesser https://doi.org/10.1038/s41612-025-01200-y
- Urgent issues regarding real-time air quality monitoring data in India: Unveiling solutions and implications for policy and health K. Vohra et al. https://doi.org/10.1016/j.aeaoa.2024.100308
- Calibrating low-cost sensors to measure vertical and horizontal gradients of NO2 and O3 pollution in three street canyons in Berlin S. Schmitz et al. https://doi.org/10.1016/j.atmosenv.2023.119830
- Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties C. Betancourt et al. https://doi.org/10.5194/gmd-15-4331-2022
- Quasi-experimentelle Evaluation der Effekte von Kiezblocks in der KiezTransform Studie N. Lünow et al. https://doi.org/10.1515/pubhef-2025-0059
- Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter M. Aix et al. https://doi.org/10.1016/j.scitotenv.2023.164063
- Remote Sensing of Tropospheric Ozone from Space: Progress and Challenges J. Xu et al. https://doi.org/10.34133/remotesensing.0178
- Applicability of compact and useful PM2.5 instrument with gas sensors in Japan and Thailand H. Aung et al. https://doi.org/10.1016/j.aeaoa.2025.100350
- Integrating Cost-Effective Measurements and CFD Modeling for Accurate Air Quality Assessment G. Ioannidis et al. https://doi.org/10.3390/atmos15091056
- Performance and data acquisition from low-cost air quality sensors: a comprehensive review M. Siddiqui et al. https://doi.org/10.1007/s11869-024-01683-3
- Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors A. Cavaliere et al. https://doi.org/10.5194/amt-16-4723-2023
- Minimized Training of Machine Learning-Based Calibration Methods for Low-Cost O3 Sensors S. Tondini et al. https://doi.org/10.1109/JSEN.2023.3339202
- How electrochemical sensors measure up to reference-grade nitrogen dioxide monitors across temporal scales S. Schmitz et al. https://doi.org/10.1016/j.scitotenv.2025.179476
- A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty S. Manu & A. Rysanek https://doi.org/10.3390/buildings14092965
- A Physics-Informed Multimodal Deep Learning Framework for City-Scale Air-Quality and Health-Risk Prediction K. Alhawiti https://doi.org/10.3390/systems14030320
- Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. https://doi.org/10.1039/D2EA00085G
21 citations as recorded by crossref.
- Time-generative AI-enabled temporal fusion transformer model for efficient air pollution sensor calibration in IIoT edge environments S. Henna et al. https://doi.org/10.3934/environsci.2025024
- Convolutional Neural Networks on Correlation between GC−MS Molecular Data and QCM Gas-Sensing Data T. Oon-pitipongsa et al. https://doi.org/10.1021/acssensors.5c03066
- Low-cost system application for policy assessment: a case study from Berlin A. Caseiro et al. https://doi.org/10.1088/2752-5309/ad56bb
- QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation S. Diez et al. https://doi.org/10.1038/s41597-024-03767-2
- Calibration and validation-based assessment of low-cost air quality sensors J. Dong et al. https://doi.org/10.1016/j.scitotenv.2025.179364
- Harness low-cost sensors for the targeted assessment of policy S. Schmitz & E. von Schneidemesser https://doi.org/10.1038/s41612-025-01200-y
- Urgent issues regarding real-time air quality monitoring data in India: Unveiling solutions and implications for policy and health K. Vohra et al. https://doi.org/10.1016/j.aeaoa.2024.100308
- Calibrating low-cost sensors to measure vertical and horizontal gradients of NO2 and O3 pollution in three street canyons in Berlin S. Schmitz et al. https://doi.org/10.1016/j.atmosenv.2023.119830
- Global, high-resolution mapping of tropospheric ozone – explainable machine learning and impact of uncertainties C. Betancourt et al. https://doi.org/10.5194/gmd-15-4331-2022
- Quasi-experimentelle Evaluation der Effekte von Kiezblocks in der KiezTransform Studie N. Lünow et al. https://doi.org/10.1515/pubhef-2025-0059
- Calibration methodology of low-cost sensors for high-quality monitoring of fine particulate matter M. Aix et al. https://doi.org/10.1016/j.scitotenv.2023.164063
- Remote Sensing of Tropospheric Ozone from Space: Progress and Challenges J. Xu et al. https://doi.org/10.34133/remotesensing.0178
- Applicability of compact and useful PM2.5 instrument with gas sensors in Japan and Thailand H. Aung et al. https://doi.org/10.1016/j.aeaoa.2025.100350
- Integrating Cost-Effective Measurements and CFD Modeling for Accurate Air Quality Assessment G. Ioannidis et al. https://doi.org/10.3390/atmos15091056
- Performance and data acquisition from low-cost air quality sensors: a comprehensive review M. Siddiqui et al. https://doi.org/10.1007/s11869-024-01683-3
- Development of low-cost air quality stations for next-generation monitoring networks: calibration and validation of NO2 and O3 sensors A. Cavaliere et al. https://doi.org/10.5194/amt-16-4723-2023
- Minimized Training of Machine Learning-Based Calibration Methods for Low-Cost O3 Sensors S. Tondini et al. https://doi.org/10.1109/JSEN.2023.3339202
- How electrochemical sensors measure up to reference-grade nitrogen dioxide monitors across temporal scales S. Schmitz et al. https://doi.org/10.1016/j.scitotenv.2025.179476
- A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty S. Manu & A. Rysanek https://doi.org/10.3390/buildings14092965
- A Physics-Informed Multimodal Deep Learning Framework for City-Scale Air-Quality and Health-Risk Prediction K. Alhawiti https://doi.org/10.3390/systems14030320
- Ambient characterisation of PurpleAir particulate matter monitors for measurements to be considered as indicative A. Caseiro et al. https://doi.org/10.1039/D2EA00085G
Saved (final revised paper)
Latest update: 07 Jun 2026
Short summary
The last 2 decades have seen substantial technological advances in the development of low-cost air pollution instruments. This study introduces a seven-step methodology for the field calibration of low-cost sensors with user-friendly guidelines, open-access code, and a discussion of common barriers. Our goal with this work is to push for standardized reporting of methods, make critical data processing steps clear for users, and encourage responsible use in the scientific community and beyond.
The last 2 decades have seen substantial technological advances in the development of low-cost...
