Preprints
https://doi.org/10.5194/amt-2021-210
https://doi.org/10.5194/amt-2021-210

  18 Aug 2021

18 Aug 2021

Review status: a revised version of this preprint was accepted for the journal AMT.

Evaluating uncertainty in sensor networks for urban air pollution insights

Daniel R. Peters1, Olalekan A. M. Popoola2, Roderic L. Jones2, Nicholas A. Martin3, Jim Mills4, Elizabeth R. Fonseca5, Amy Stidworthy6, Ella Forsyth6, David Carruthers6, Megan Dupuy-Todd1,a, Felicia Douglas5, Katie Moore1,b, Rishabh U. Shah1, Lauren E. Padilla1, and Ramón A. Alvarez1 Daniel R. Peters et al.
  • 1Environmental Defense Fund, 301 Congress Ave #1300, Austin, TX 78701, USA
  • 2Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK
  • 3Air Quality and Aerosol Metrology Group, Atmospheric Environmental Science Department, National Physical Laboratory, Hampton Road, Teddington, Middlesex, TW11 0LW, UK
  • 4ACOEM Air Monitors Ltd., Ground Floor Offices, C1 The Courtyard, Tewkesbury Business Park, Tewkesbury, Gloucestershire, GL20 8GD, UK
  • 5Environmental Defense Fund Europe, 3 rd Floor, 41 Eastcheap, London, EC3M 1DT, UK
  • 6Cambridge Environmental Research Consultants Ltd., 3 King's Parade, Cambridge, CB2 1SJ, UK
  • anow at: Clean Air Task Force, 114 State Street, 6th Floor, Boston, MA 02109, USA
  • bnow at: Clarity Movement Co., 808 Gilman Street, Berkeley, CA 94710, USA

Abstract. Ambient air pollution poses a major global public health risk. Lower-cost air quality sensors (LCS) are increasingly being explored as a tool to understand local air pollution problems and develop effective solutions. A barrier to LCS adoption is potentially larger measurement uncertainty compared to reference measurement technology. The technical performance of various LCS has been tested in laboratory and field environments, and a growing literature on uses of LCS primarily focuses on proof-of-concept deployments. However, few studies have demonstrated the implications of LCS measurement uncertainties on a sensor network’s ability to assess spatiotemporal patterns of local air pollution. Here, we present results from a 2-year deployment of 100 stationary electrochemical nitrogen dioxide (NO2) LCS across Greater London as part of the Breathe London pilot project (BL). We evaluated sensor performance using collocations with reference instruments, estimating ~35 % average uncertainty (root-mean-square error) of the calibrated LCS, and identified infrequent, multi-week periods of poorer performance and high bias during summer months. We analyzed BL data to generate insights about London’s air pollution, including long-term concentration trends, diurnal and day-of-week patterns, and profiles of elevated concentrations during regional pollution episodes. These findings were validated against measurements from an extensive reference network, demonstrating the BL network’s ability to generate robust information about London’s air pollution. In cases where the BL network did not effectively capture features that the reference network measured, ongoing collocations of representative sensors often provided evidence of irregularities in sensor performance, demonstrating how, in the absence of an extensive reference network, project-long collocations could enable characterization and mitigation of network-wide sensor uncertainties. The conclusions are restricted to the specific sensors used for this study, but the results give direction to LCS users by demonstrating the kinds of air pollution insights possible from LCS networks and provide a blueprint for future LCS projects to manage and evaluate uncertainties when collecting, analyzing and interpreting data.

Daniel R. Peters et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on amt-2021-210', Laurent Spinelle, 24 Aug 2021
    • EC1: 'Reply on RC1', Dominik Brunner, 25 Sep 2021
    • AC1: 'Response to Reviewer 1', Daniel Peters, 29 Oct 2021
  • RC2: 'Comment on amt-2021-210', Anonymous Referee #2, 11 Sep 2021
    • AC2: 'Response to Reviewer 2', Daniel Peters, 29 Oct 2021

Daniel R. Peters et al.

Daniel R. Peters et al.

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Short summary
We present more than two 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.