Articles | Volume 12, issue 2
https://doi.org/10.5194/amt-12-1325-2019
https://doi.org/10.5194/amt-12-1325-2019
Research article
 | 
28 Feb 2019
Research article |  | 28 Feb 2019

An improved low-power measurement of ambient NO2 and O3 combining electrochemical sensor clusters and machine learning

Kate R. Smith, Peter M. Edwards, Peter D. Ivatt, James D. Lee, Freya Squires, Chengliang Dai, Richard E. Peltier, Mat J. Evans, Yele Sun, and Alastair C. Lewis

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Cited articles

Broday, D. M., Arpaci, A., Bartonova, A., Castell-Balaguer, N., Cole-Hunter, T., Dauge, F. R., Fishbain, B., Jones, R. L., Galea, K., Jovasevic-Stojanovic, M., Kocman, D., Martinez-Iñiguez, T., Nieuwenhuijsen, M., Robinson, J., Svecova, V., and Thai, P.: Wireless distributed environmental sensor networks for air pollution measurement-the promise and the current reality, Sensors, 17, 2263, https://doi.org/10.3390/s17102263, 2017. 
Caron, A., Redon, N., Hanoune, B., and Coddeville, P.: Performances and limitations of electronic gas sensors to investigate an indoor air quality event, Build. Environ., 107, 19–28, https://doi.org/10.1016/j.buildenv.2016.07.006, 2016. 
Chan, C. K. and Yao, X.: Air pollution in mega cities in China, Atmos. Environ., 42, 1–42, https://doi.org/10.1016/j.atmosenv.2007.09.003, 2008. 
Chen, T. and Guestrin, C.: XGBoost: A Scalable Tree Boosting System, Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '16, 13–17 August 2016 San Francisco, CA, USA, https://doi.org/10.1145/2939672.2939785, 2016. 
Edwards, P., Smith, K., Lewis, A., and Ivatt, P.: Low cost sensor in field calibrations (training and test data) – Beijing 2017, https://doi.org/10.15124/1a0c64b0-433b-4eec-b5c7-64d3de0a0351, 2017. 
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Short summary
Clusters of low-cost, low-power atmospheric gas sensors were built into a sensor instrument to monitor NO2 and O3 in Beijing, alongside reference instruments, aiming to improve the reliability of sensor measurements. Clustering identical sensors and using the median sensor signal was used to minimize drift over short and medium timescales. Three different machine learning techniques were used for all the sensor data in an attempt to correct for cross-interferences, which worked to some degree.
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