Performance evaluation of low-cost air quality sensors: A review

Ye Kang; Lu Aye; Tuan Duc Ngo; Jin Zhou

doi:10.1016/j.scitotenv.2021.151769

Performance evaluation of low-cost air quality sensors: A review

Sci Total Environ. 2022 Apr 20:818:151769. doi: 10.1016/j.scitotenv.2021.151769. Epub 2021 Nov 19.

Authors

Ye Kang¹, Lu Aye², Tuan Duc Ngo², Jin Zhou³

Affiliations

¹ Department of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia.
² Department of Infrastructure Engineering, Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, Victoria 3010, Australia.
³ Department of Civil Engineering, Monash University, Clayton, Victoria 3800, Australia. Electronic address: Jenny.zhou@monash.edu.

PMID: 34801495
DOI: 10.1016/j.scitotenv.2021.151769

Abstract

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, r²; 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 r² 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 r² 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.

Keywords: Environmental setting; Pollutant attribute; Reference instrument; Regression model; Sensor original equipment manufacturer (OEM) specification; Statistical measure.

Publication types

Review

MeSH terms

Air Pollutants* / analysis
Air Pollution* / analysis
Environmental Monitoring / methods
Particulate Matter / analysis
Reproducibility of Results

Substances

Air Pollutants
Particulate Matter