Articles | Volume 21, issue 9
https://doi.org/10.5194/acp-21-7199-2021
https://doi.org/10.5194/acp-21-7199-2021
Research article
 | 
11 May 2021
Research article |  | 11 May 2021

Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: impacts of COVID-19 pandemic lockdown

Shibao Wang, Yun Ma, Zhongrui Wang, Lei Wang, Xuguang Chi, Aijun Ding, Mingzhi Yao, Yunpeng Li, Qilin Li, Mengxian Wu, Ling Zhang, Yongle Xiao, and Yanxu Zhang

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Cited articles

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Apte, J. S., Messier, K. P., Gani, S., Brauer, M., Kirchstetter, T. W., Lunden, M. M., Marshall, J. D., Portier, C. J., Vermeulen, R. C. H., and Hamburg, S. P.: High-resolution air pollution mapping with google street view cars: exploiting big data, Environ. Sci. Technol., 51, 6999–7008, https://doi.org/10.1021/acs.est.7b00891, 2017. 
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Bao, R. and Zhang, A.: Does lockdown reduce air pollution? Evidence from 44 cities in northern China, Sci. Total Environ., 139052, https://doi.org/10.1016/j.scitotenv.2020.139052, 2020. 
Short summary
Mobile monitoring with low-cost sensors is a promising approach to garner high-spatial-resolution observations representative of the community scale. We develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3) based on GIS technology. Our results demonstrate the sensing power of mobile monitoring for urban air pollution, which provides detailed information for source attribution and accurate traceability at the urban micro-scale.
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