Journal
SCIENCE OF THE TOTAL ENVIRONMENT
Volume 818, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.scitotenv.2021.151769
Keywords
Statistical measure; Environmental setting; Pollutant attribute; Snsor original equipment manufacturer; (OEM) specification; Reference instrument; Regression model
Categories
Funding
- Building 4.0 CRC program and Commonwealth Scientific and Industrial Research Organisation
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This review examines the methodologies and influential factors in evaluating the performance of low-cost air quality sensors. The study finds that stable environmental settings and the use of advanced regression models can improve sensor performance. However, the effects of pollutant attributes and sensor OEM specifications are inconclusive.
The monitoring of air quality compliance requires the use of Federal Reference Methods (FRM)/Federal Equivalent Methods (FEM); nevertheless, the validity and reliability of low-cost sensors deserve attention due to their affordability and accessibility. This review examines the methodologies of previous studies to characterise the performance of low-cost air quality sensors and to identify the influential factors in sensor evaluation experiments. The data on four statistical measures (Correlation of Determination, r(2); Root Mean Square Error, RMSE; Mean Normalised Bias, MNB; and Coefficient of Variation, CV) and details about five methodological factors in experimental design (environmental setting, reference instrument, regression model, pollutant attribute, and sensor original equipment manufacturer (OEM) specification) were extracted from a total of 112 primary articles for a detailed analysis. The results of the analysis suggested that low-cost air quality sensors exhibited improved r(2) and RMSE in the experiments with stable environmental settings, in the comparison against non-designated reference instruments, or in the analysis where advanced regression models were used to adjust the sensor readings. However, the pollutant attribute and sensor OEM specification had inconclusive effects on r(2) and RMSE due to contradictory results and lack of sufficient data. MNB and CV, two measures that US EPA recommends to determine the suitable application tier of air quality sensors, varied significantly among published experiments due to the discrepancy in experimental design. The outcomes of this work could provide direction to researchers regarding sensor evaluation experiments and guide practitioners to effectively select and deploy low-cost sensors for air quality monitoring. (c) 2021 Elsevier B.V. All rights reserved.
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