Articles | Volume 15, issue 2
https://doi.org/10.5194/amt-15-321-2022
© Author(s) 2022. 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-15-321-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Jan 2022
Research article |
| 21 Jan 2022
| 21 Jan 2022
Evaluating uncertainty in sensor networks for urban air pollution insights
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
Olalekan A. M. Popoola
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Roderic L. Jones
Yusuf Hamied Department of Chemistry, University of Cambridge,
Cambridge, CB2 1EW, UK
Nicholas A. Martin
Air Quality and Aerosol Metrology Group, Atmospheric Environmental
Science Department, National Physical Laboratory, Hampton Road, Teddington,
Middlesex, TW11 0LW, UK
Jim Mills
ACOEM Air Monitors Ltd., Ground Floor Offices, C1 The Courtyard,
Tewkesbury Business Park, Tewkesbury, Gloucestershire, GL20 8GD, UK
Elizabeth R. Fonseca
Environmental Defense Fund Europe, 3rd Floor, 41 Eastcheap,
London, EC3M 1DT, UK
Amy Stidworthy
Cambridge Environmental Research Consultants Ltd., 3 King's Parade,
Cambridge, CB2 1SJ, UK
Ella Forsyth
Cambridge Environmental Research Consultants Ltd., 3 King's Parade,
Cambridge, CB2 1SJ, UK
David Carruthers
Cambridge Environmental Research Consultants Ltd., 3 King's Parade,
Cambridge, CB2 1SJ, UK
Megan Dupuy-Todd
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
now at: Clean Air Task Force, 114 State Street, 6th Floor, Boston, MA
02109, USA
Felicia Douglas
Environmental Defense Fund Europe, 3rd Floor, 41 Eastcheap,
London, EC3M 1DT, UK
Katie Moore
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
now at: Clarity Movement Co., 808 Gilman Street, Berkeley, CA 94710,
USA
Rishabh U. Shah
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
Lauren E. Padilla
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
Ramón A. Alvarez
Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX
78701, USA
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Cited
11 citations as recorded by crossref.
- Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area R. Shah et al. 10.1021/acs.est.2c08096
- RPCA-based techniques for pattern extraction, hotspot identification and signal correction using data from a dense network of low-cost NO2 sensors in London M. Bogaert et al. 10.1016/j.scitotenv.2024.171522
- Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science J. Hofman et al. 10.3390/s24175653
- Smart cities software applications for sustainability and resilience D. Okonta & V. Vukovic 10.1016/j.heliyon.2024.e32654
- Low‐cost air quality monitoring networks for long‐term field campaigns: A review F. Carotenuto et al. 10.1002/met.2161
- Challenges and Opportunities in Calibrating Low-Cost Environmental Sensors N. Nalakurthi et al. 10.3390/s24113650
- How standardizing ‘low-cost’ air quality monitors will help measure pollution R. Brown & N. Martin 10.1038/s42254-023-00561-8
- Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al. 10.1039/D2EA00165A
- In situ drift correction for a low-cost NO2 sensor network J. Miech et al. 10.1039/D2EA00145D
- Air pollution measurement errors: is your data fit for purpose? S. Diez et al. 10.5194/amt-15-4091-2022
- Condensation particle counters: Exploring the limits of miniaturisation S. Balendra et al. 10.1016/j.jaerosci.2023.106266
11 citations as recorded by crossref.
- Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area R. Shah et al. 10.1021/acs.est.2c08096
- RPCA-based techniques for pattern extraction, hotspot identification and signal correction using data from a dense network of low-cost NO2 sensors in London M. Bogaert et al. 10.1016/j.scitotenv.2024.171522
- Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science J. Hofman et al. 10.3390/s24175653
- Smart cities software applications for sustainability and resilience D. Okonta & V. Vukovic 10.1016/j.heliyon.2024.e32654
- Low‐cost air quality monitoring networks for long‐term field campaigns: A review F. Carotenuto et al. 10.1002/met.2161
- Challenges and Opportunities in Calibrating Low-Cost Environmental Sensors N. Nalakurthi et al. 10.3390/s24113650
- How standardizing ‘low-cost’ air quality monitors will help measure pollution R. Brown & N. Martin 10.1038/s42254-023-00561-8
- Evaluation of low-cost gas sensors to quantify intra-urban variability of atmospheric pollutants A. Baruah et al. 10.1039/D2EA00165A
- In situ drift correction for a low-cost NO2 sensor network J. Miech et al. 10.1039/D2EA00145D
- Air pollution measurement errors: is your data fit for purpose? S. Diez et al. 10.5194/amt-15-4091-2022
- Condensation particle counters: Exploring the limits of miniaturisation S. Balendra et al. 10.1016/j.jaerosci.2023.106266
Latest update: 13 Dec 2024
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.
We present more than 2 years of NO2 pollution measurements from a sensor network in Greater...
