Design, calibration, and testing of a mobile sensor system for air pollution and built environment data collection: The urban scanner platform. (15th January 2023)

• Record Type: Journal Article
• Authors: Ganji, Arman; Youssefi, Omid; Xu, Junshi; Mallinen, Keni; Lloyd, Marshall; Wang, An; Bakhtari, Ardevan; Weichenthal, Scott; Hatzopoulou, Marianne
• Is Part Of: Environmental pollution. Volume 317(2023)
• Publication Date: 2023-01-15
• Subjects: Urban scanner -- Air pollution -- Mobile sampling -- Sensor calibration; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2022.120720
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: This paper describes a mobile air pollution sampling system, the Urban Scanner, which aims at gathering dense spatiotemporal air quality data to support urban air quality and exposure science. Urban Scanner comprises custom vehicle-mounted sensors for air pollution, meteorology, and built environment data collection (low-cost sensors, wind anemometer, 360 deg camera, LIDAR, GPS) as well as a server to store, process, and map all gathered geo-referenced sensory information. Two levels of sensor calibration were implemented, both in a chamber and in the field, against reference instrumentation. Chamber tests and a set of mathematical tools were developed to correct for sensor noise (wavelet denoising), misalignment (linear and nonlinear), and hysteresis removal. Models based on chamber testing were further refined based on field co-location. While field co-location captures natural changes in air pollution and meteorology, chamber tests allow for simulating fast transitions in these variables, like the transitions experienced by a mobile sensor in an urban environment. The best suite of models achieved an R 2 higher than 0.9 between sensor output and reference station observations and an RMSE of 2.88 ppb for nitrogen dioxide and 4.03 ppb for ozone. A mobile sampling campaign was conducted in the city of Toronto, Canada, to further test Urban Scanner. We observe that the platform adequately captures spatial and temporal variability in urban air pollution, leading to the development of land-use regression models with high explanatory power. Graphical abstract: Image 1 Highlights: Urban Scanner is a mobile monitoring system for air quality and built environment. It includes low-cost sensors and ancillary instruments on the vehicle rooftop. Algorithms were developed to remove noise and hysteresis from signals. Sensor calibration took place in a chamber and in the field. The system's capability was demonstrated through a one-year sampling campaign.