Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 14, issue 8
Articles | Volume 14, issue 8
https://doi.org/10.5194/amt-14-5637-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-5637-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 8
Research article
 | 
18 Aug 2021
Research article |  | 18 Aug 2021

Machine learning calibration of low-cost NO2 and PM10 sensors: non-linear algorithms and their impact on site transferability

Peer Nowack, Lev Konstantinovskiy, Hannah Gardiner, and John Cant

Related authors

Tropospheric ozone trends and attributions over East and Southeast Asia in 1995–2019: an integrated assessment using statistical methods, machine learning models, and multiple chemical transport models
Xiao Lu, Yiming Liu, Jiayin Su, Xiang Weng, Tabish Ansari, Yuqiang Zhang, Guowen He, Yuqi Zhu, Haolin Wang, Ganquan Zeng, Jingyu Li, Cheng He, Shuai Li, Teerachai Amnuaylojaroen, Tim Butler, Qi Fan, Shaojia Fan, Grant L. Forster, Meng Gao, Jianlin Hu, Yugo Kanaya, Mohd Talib Latif, Keding Lu, Philippe Nédélec, Peer Nowack, Bastien Sauvage, Xiaobin Xu, Lin Zhang, Ke Li, Ja-Ho Koo, and Tatsuya Nagashima
Atmos. Chem. Phys., 25, 7991–8028, https://doi.org/10.5194/acp-25-7991-2025,https://doi.org/10.5194/acp-25-7991-2025, 2025
Short summary
Constraining uncertainty in projected precipitation over land with causal discovery
Kevin Debeire, Lisa Bock, Peer Nowack, Jakob Runge, and Veronika Eyring
Earth Syst. Dynam., 16, 607–630, https://doi.org/10.5194/esd-16-607-2025,https://doi.org/10.5194/esd-16-607-2025, 2025
Short summary
Opinion: Why all emergent constraints are wrong but some are useful – a machine learning perspective
Peer Nowack and Duncan Watson-Parris
Atmos. Chem. Phys., 25, 2365–2384, https://doi.org/10.5194/acp-25-2365-2025,https://doi.org/10.5194/acp-25-2365-2025, 2025
Short summary
Exploring Ozone-climate Interactions in Idealized CMIP6 DECK Experiments
Jingyu Wang, Gabriel Chiodo, Timofei Sukhodolov, Blanca Ayarzagüena, William T. Ball, Mohamadou Diallo, Birgit Hassler, James Keeble, Peer Nowack, Clara Orbe, and Sandro Vattioni
EGUsphere, https://doi.org/10.5194/egusphere-2025-340,https://doi.org/10.5194/egusphere-2025-340, 2025
Short summary
The importance of stratocumulus clouds for projected warming patterns and circulation changes
Philipp Breul, Paulo Ceppi, and Peer Nowack
EGUsphere, https://doi.org/10.5194/egusphere-2025-221,https://doi.org/10.5194/egusphere-2025-221, 2025
Short summary
More articles (7)

Cited articles

Bishop, C. M.: Pattern recognition and machine learning, Springer Science+Business Media, Singapore, 2006. a, b
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, https://doi.org/10.1201/9780429469275-8, 2001. a, b
Breiman, L. and Friedman, J. H.: Predicting multivariate responses in multiple linear regression, J. Roy. Stat. Soc.-B, 59, 3–54, https://doi.org/10.1111/1467-9868.00054, 1997. a
Casey, J. G. and Hannigan, M. P.: Testing the performance of field calibration techniques for low-cost gas sensors in new deployment locations: across a county line and across Colorado, Atmos. Meas. Tech., 11, 6351–6378, https://doi.org/10.5194/amt-11-6351-2018, 2018. a, b
Casey, J. G., Collier-Oxandale, A., and Hannigan, M.: Performance of artificial neural networks and linear models to quantify 4 trace gas species in an oil and gas production region with low-cost sensors, Sensor. Actuat. B-Chem., 283, 504–514, https://doi.org/10.1016/j.snb.2018.12.049, 2019. a
More articles (44)
Download
Short summary
Machine learning (ML) calibration techniques could be an effective way to improve the performance of low-cost air pollution sensors. Here we provide novel insights from case studies within the urban area of London, UK, where we compared the performance of three ML techniques to calibrate low-cost measurements of NO2 and PM10. In particular, we highlight the key issue of the method-dependent robustness in maintaining calibration skill after transferring sensors to different measurement sites.
Read more
Share