Evaluation of field calibration methods and performance of AQMesh, a low-cost air quality monitor
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Published:2021-04-08
Issue:5
Volume:193
Page:
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ISSN:0167-6369
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Container-title:Environmental Monitoring and Assessment
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language:en
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Short-container-title:Environ Monit Assess
Author:
Wahlborg DanORCID, Björling MikaelORCID, Mattsson MagnusORCID
Abstract
AbstractField calibrations of NO2, NO, and PM10 from AQMesh Air Quality Monitors (AQMs) were conducted during a summer and an autumn period in a busy street in a midsize Swedish city. All the three linear calibration procedures studied (postscaled, bisquare, and orthogonal data) significantly reduced the ranges and magnitudes of the performance indicators to yield more reliable results than the raw data. The improvements were sufficient to satisfy the European Union (EU) Data Quality Objective (DQO) for indicative measurements as compared to reference data only for NO2 (above 50 µg m−3) and NO (above 30 µg m−3) during the autumn calibration period. The relatively simple bisquare procedure had the best performance overall. The bisquare procedure improved the root mean square error by the same amount as other studies using complex multivariate calibration methods. Low concentrations of pollutants were measured, far below the EU Environmental Quality Standard thresholds and even satisfying the future goals for the Environmental Quality Objectives. Cleaning the raw data by removing data points in the reference data that were below the reference station limit of detections (and the synchronous data points in the AQM prescaled data) was found to improve the performances of the calibration procedures appreciably. Many NO2 and almost all PM10 data points in this study fell below the AQM limit of detection. These low concentrations will probably be a common problem in many field studies, at least in areas with relatively low air pollution. However, the relative errors were sufficiently low for these data points that they could be interpreted as accurately representing low concentrations and did not need to be removed from the datasets. For the NO2 measurements, a slight periodic error correlated with sunlight and increased ambient temperature was noted. NO measurements correlated strongly with increased traffic.
Funder
University of Gävle
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Pollution,General Environmental Science,General Medicine
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