Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?
By N. Castell, F. Dauge, P. Schneider, M. Vogt, U. Lerner, B. Fishbain, D. Broday, A. Bartoňová. Environment International, 2017
893 citations recorded by the source corpus.
The emergence of low-cost, user-friendly and very compact air pollution platforms enable observations at high spatial resolution in near-real-time and provide new opportunities to simultaneously enhance existing monitoring systems, as well as engage citizens in active environmental monitoring. This provides a whole new set of capabilities in the assessment of human exposure to air pollution. However, the data generated by these platforms are often of questionable quality. We have conducted an exhaustive evaluation of 24 identical units of a commercial low-cost sensor platform against CEN (European Standardization Organization) reference analyzers, evaluating their measurement capability over time and a range of environmental conditions. Our results show that their performance varies spatially and temporally, as it depends on the atmospheric composition and the meteorological conditions. Our results show that the performance varies from unit to unit, which makes it necessary to examine the data quality of each node before its use. In general, guidance is lacking on how to test such sensor nodes and ensure adequate performance prior to marketing these platforms. We have implemented and tested diverse metrics in order to assess if the sensor can be employed for applications that require high accuracy (i.e., to meet the Data Quality Objectives defined in air quality legislation, epidemiological studies) or lower accuracy (i.e., to represent the pollution level on a coarse scale, for purposes such as awareness raising). Data quality is a pertinent concern, especially in citizen science applications, where citizens are collecting and interpreting the data. In general, while low-cost platforms present low accuracy for regulatory or health purposes they can provide relative and aggregated information about the observed air quality.
Subfields: Atmospheric Science, Environmental Engineering, Health, Toxicology and Mutagenesis
View Paper: https://www.semanticscholar.org/paper/c2306f1768eea9113d08a88df8e6f7b46bef5e0c
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In Atmospheric Science
Citations in the corpus
- Evaluation of PM2.5 measured in an urban setting using a low-cost optical particle counter and a Federal Equivalent Method Beta Attenuation Monitor (2020, background): “The rise of low-cost, readily deployable air monitoring instrumentation provides a pathway to enhance citizen science and engagement (Castell et al. 2017; Schneider et al. 2017), and potentially offer insights at finer spatial scales beyond any established regulatory monitoring network (Kaufman et…”
- Applications of low-cost sensing technologies for air quality monitoring and exposure assessment: How far have they gone? (2018, methodology): “Of the reviewed studies, five monitored particulate matter concentration (Castell et al., 2017; Gao et al., 2015; Jiao et al., 2016; Olivares and Edwards, 2015; Zikova et al., 2017).”
- Review of the Performance of Low-Cost Sensors for Air Quality Monitoring (2019, background): “NO electrochemical 44 6 Jiao [39], Bigi [42], Karagulian [22], Mead [44], Popoola [45], AQ-SPEC [19], Castell [10], Borrego [53], Cross [58], Gillooly [60], Spinelle [24], Gerboles [23], Wei [59], Crunaire [33]”