In order to answer this, the user mustįirst clearly define the question that is to be asked of the data, and thus Technology is whether the data provided are fit for purpose (Andrewes et al., 2021 Lewis and Edwards, 2016). Key question that needs to be asked when choosing a particular measurement Through to large, expensive reference and research-grade instrumentation. Low-cost devices that can be carried on an individual's person all the way
Now available for this purpose (Morawska et al., 2018), ranging from small (LCS) based technologies means a growing number of measurement devices are Human exposure (Molina and Molina, 2004). The measurement of air pollutants is central to our ability to both deviseĪnd assess the effectiveness of policies to improve air quality and reduce Measurements as part of the QUANT project, and discuss the implications this Measurements, using a selection of LCS deployed alongside reference With this insight we demonstrate the impact these errors can have on Potentially more insightful approaches to assess measurement performance. Implications they have on traditional metrics and other empirical, Nature of common air pollution measurement errors is investigated, and the But the use of these metrics can be limited,Īnd even misleading, restricting our understanding of the error structureĪnd therefore the measurements' information content. Only use these metrics when trying to define the most appropriate sensor Colocation studies areĬomplex and time-consuming, and it is easy to fall into the temptation to Performance metrics ( R 2, RMSE, MAE, etc.). These colocation performance assessments is the exacerbated use of global
A problem that obscures much of the information content of Non-trivial to interpret and often difficult to extrapolate to future device Information on measurement device error structure, but the results are Despite the limitations, colocation studies do provide useful Glimpse of LCS performance in specific conditions over a limited period of Characterising LCS performance thus currentlyĭepends primarily on colocation studies with reference instruments, whichĪre very expensive and do not offer a definitive solution but rather a The advent of LCS has provided a challenge in that manyĮrror sources show high spatial and temporal variability, making laboratoryĭerived corrections difficult. Measurements suffer from errors, with the degree to which these errors impact theĪccuracy of the final data often determined by our ability to identify andĬorrect for them. This, end users need to clearly identify the data requirements a priori andĭesign quantifiable success criteria by which to judge the data. Widespread emergence of low cost sensors (LCS) to measure air quality. When making measurements of air quality, having a reliableĮstimate of the measurement uncertainty is key to assessing the informationĬontent that an instrument is capable of providing, and thus its usefulness
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