On the Feasibility of Measuring Urban Air Pollution by Wireless Distributed Sensor Networks
Overview
Affiliations
Accurate evaluation of air pollution on human-wellbeing requires high-resolution measurements. Standard air quality monitoring stations provide accurate pollution levels but due to their sparse distribution they cannot capture the highly resolved spatial variations within cities. Similarly, dedicated field campaigns can use tens of measurement devices and obtain highly dense spatial coverage but normally deployment has been limited to short periods of no more than few weeks. Nowadays, advances in communication and sensory technologies enable the deployment of dense grids of wireless distributed air monitoring nodes, yet their sensor ability to capture the spatiotemporal pollutant variability at the sub-neighborhood scale has never been thoroughly tested. This study reports ambient measurements of gaseous air pollutants by a network of six wireless multi-sensor miniature nodes that have been deployed in three urban sites, about 150 m apart. We demonstrate the network's capability to capture spatiotemporal concentration variations at an exceptional fine resolution but highlight the need for a frequent in-situ calibration to maintain the consistency of some sensors. Accordingly, a procedure for a field calibration is proposed and shown to improve the system's performance. Overall, our results support the compatibility of wireless distributed sensor networks for measuring urban air pollution at a sub-neighborhood spatial resolution, which suits the requirement for highly spatiotemporal resolved measurements at the breathing-height when assessing exposure to urban air pollution.
Apostolopoulos I, Androulakis S, Kalkavouras P, Fouskas G, Pandis S Sensors (Basel). 2024; 24(13).
PMID: 39000888 PMC: 11244084. DOI: 10.3390/s24134110.
Leveraging low-cost sensors to predict nitrogen dioxide for epidemiologic exposure assessment.
Zuidema C, Bi J, Burnham D, Carmona N, Gassett A, Slager D J Expo Sci Environ Epidemiol. 2024; .
PMID: 38589565 DOI: 10.1038/s41370-024-00667-w.
Jain S, Gardner-Frolick R, Martinussen N, Jackson D, Giang A, Zimmerman N Geohealth. 2024; 8(2):e2023GH000935.
PMID: 38361590 PMC: 10867477. DOI: 10.1029/2023GH000935.
Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors.
Samad A, Kieser J, Chourdakis I, Vogt U Sensors (Basel). 2024; 24(3).
PMID: 38339662 PMC: 10857248. DOI: 10.3390/s24030945.
Feldman A, Kendler S, Marshall J, Kushwaha M, Sreekanth V, Upadhya A Environ Sci Technol. 2023; 58(1):480-487.
PMID: 38104325 PMC: 10785748. DOI: 10.1021/acs.est.3c04495.