Articles | Volume 15, issue 2
https://doi.org/10.5194/amt-15-321-2022
https://doi.org/10.5194/amt-15-321-2022
Research article
 | 
21 Jan 2022
Research article |  | 21 Jan 2022

Evaluating uncertainty in sensor networks for urban air pollution insights

Daniel R. Peters, Olalekan A. M. Popoola, Roderic L. Jones, Nicholas A. Martin, Jim Mills, Elizabeth R. Fonseca, Amy Stidworthy, Ella Forsyth, David Carruthers, Megan Dupuy-Todd, Felicia Douglas, Katie Moore, Rishabh U. Shah, Lauren E. Padilla, and Ramón A. Alvarez

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Cited articles

Apte, J. S., Messier, K. P., Gani, S., Brauer, M., Kirchstetter, T. W., Lunden, M. M., Marshall, J. D., Portier, C. J., Vermeulen, R. C. H., and Hamburg, S. P.: High-resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data, Environ. Sci. Technol., 51, 6999–7008, https://doi.org/10.1021/acs.est.7b00891, 2017. 
AQMesh: https://www.aqmesh.com/products/aqmesh/, last access: 15 June 2021. 
AQ-SPEC: AQMesh (v.4.0) – field evaluation, South Coast AQMD, available at: http://www.aqmd.gov/aq-spec/sensordetail/aqmesh-(v.4.0) (last access: 7 January 2022), Diamond Bar, CA, 2015. 
Bi, J., Stowell, J., Seto, E. Y. W., English, P. B., Al-Hamdan, M. Z., Kinney, P. L., Freedman, F. R., and Liu, Y.: Contribution of low-cost sensor measurements to the prediction of PM2.5 levels: A case study in Imperial County, California, USA, Environ. Res., 180, 108810, https://doi.org/10.1016/j.envres.2019.108810, 2020. 
Breathe London: AQMesh fixed sensor network data quality assurance and control procedures, available at: https://www.globalcleanair.org/files/2021/01/Breathe-London-Fixed-Sensor-Network-QAQC-Procedures.pdf (last access: 7 January 2022), 2020. 
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Short summary
We present more than 2 years of NO2 pollution measurements from a sensor network in Greater London and compare results to an extensive network of expensive reference-grade monitors. We show the ability of our lower-cost network to generate robust insights about local air pollution. We also show how irregularities in sensor performance lead to some uncertainty in results and demonstrate ways that future users can characterize and mitigate uncertainties to get the most value from sensor data.
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