Evaluating the Performance of Low-cost PM Sensors over Multiple COALESCE Network Sites

Air quality is a global concern, with particulate matter receiving considerable attention due to its impact on human health and climate change. Recent advances in low-cost sensors allow their deployment in large number to measure spatio-temporal and real-time air quality data. Low-cost sensors need...

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Veröffentlicht in:Aerosol and Air Quality Research 2023-05, Vol.23 (5), p.1-22+ap5
Hauptverfasser: Dharaiya, Vishal R., Malyan, Vasudev, Kumar, Vikas, Sahu, Manoranjan, Venkatraman, Chandra, Biswas, Pratim, Yadav, Kajal, Haswani, Diksha, Raman, Ramya Sunder, Bhat, Ruqia, Najar, Tanveer Ahmad, Jehangir, Arshid, Patil, Rohit P., Pandithurai, G., Duhan, Sandeep Singh, Laura, Jitendra Singh
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Sprache:eng
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Zusammenfassung:Air quality is a global concern, with particulate matter receiving considerable attention due to its impact on human health and climate change. Recent advances in low-cost sensors allow their deployment in large number to measure spatio-temporal and real-time air quality data. Low-cost sensors need careful evaluation with both regulatory approved methods and other data sets to understand their efficacy. In this work, PM concentrations measured by deploying low-cost sensors at four regional sites are evaluated through comparison with satellite-based model MERRA-2 and the SASS reference instrument. Daily PM_(2.5) mass concentration variation was analyzed at four regional sites of India from January 2020 to July 2020, including pre-lockdown and six different lockdown periods. Higher PM_(2.5) concentration was observed at Rohtak (119 μg m^(-3)) compared to Mahabaleshwar (33 μg m^(-3)), Bhopal (45 μg m^(-3)) and Kashmir sites during the pre-lock down period. During the lockdown period, the PM_(2.5) mass concentration was reduced significantly compared to the pre-lockdown period at every location, although the PM_(2.5) concentration was different at each location. The air quality trend was quite similar in both the measurements, however, MERRA-2 reconstructed PM_(2.5) was significantly lower in the pre-lockdown period compared to the lockdown periods. Significant differences were observed between low-cost sensor measurements and MERRA-2 reanalysis data. These are attributed to the MERRA-2 modelling analysis that measures less PM_(2.5) concentration as compared to ground-based measurements, whereas low-cost sensor are ground-based measurements but needs corrections as it is subject to the calibration dependencies and biases.
ISSN:1680-8584
2071-1409
DOI:10.4209/aaqr.220390