Preprints
https://doi.org/10.5194/egusphere-2024-1685
https://doi.org/10.5194/egusphere-2024-1685
19 Jun 2024
 | 19 Jun 2024
Status: this preprint is open for discussion and under review for Atmospheric Measurement Techniques (AMT).

Performance Evaluation of Atmotube Pro sensors for Air Quality Measurements

Aishah Shittu, Kirsty Pringle, Stephen Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid

Abstract. This study presents a performance evaluation of eight Atmotube Pro sensors using US Environmental Protection Agency (US-EPA) guidelines. The Atmotube Pro sensors were collocated side-by-side with a reference-grade FIDAS monitor in an outdoor setting for a 14-week period. The result of the assessment showed the Atmotube Pro sensors had a coefficient of variation (CoV) of 23 %, 15 % and 13 % for minutes, hourly and daily PM2.5 data averages, respectively. The PM2.5 data was cleaned prior to analysis to improve reproducibility between units. 6 out of 8 Atmotube Pro sensor units had particularly good precision. The inter-sensor variability assessment showed two sensors with low bias and one sensor with a higher bias in comparison with the sensor average. Simple univariate analysis was sufficient to obtain good fitting quality to a FIDAS reference-grade monitor (R2 > 0.7) at hourly averages although, poorer performance was observed using a higher time resolution of 15 minutes averaged PM2.5 data (R2; 0.43–0.54). The average error bias, root mean square error (RMSE) and normalized root mean square error (NRMSE) were 4.19 µgm-3 and 2.17 % respectively. While there were negligible influences of temperature on Atmotube Pro measured PM2.5 values, substantial positive biases (compared to a reference instrument) occurred at relative humidity (RH) values > 80 %. The Atmotube Pro sensors correlated well with the purple air sensor (R2=0.86, RMSE=2.85 µgm-3). In general, the Atmotube Pro sensors performed well and passed the base testing metrics as stipulated by recommended guidelines for low-cost PM2.5 sensors.

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Aishah Shittu, Kirsty Pringle, Stephen Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid

Status: open (until 13 Aug 2024)

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Aishah Shittu, Kirsty Pringle, Stephen Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid

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Sensor data with reference Aishah Shittu, Kirsty Pringle, Steve Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid https://zenodo.org/records/11059054

Aishah Shittu, Kirsty Pringle, Stephen Arnold, Richard Pope, Ailish Graham, Carly Reddington, Richard Rigby, and James McQuaid

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Short summary
The study highlighted the importance of data cleaning in improving the raw Atmotube Pro PM2.5 data. The data cleaning method was successful in improving the inter-sensor variability among the Atmotube Pro sensors data. This study showed 62.5 % of the sensors used for the study exhibited greater precision in their measurements. The overall performance showed the sensors passed the base testing recommended by USEPA using one-hour averaged data.