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High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network

Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide...

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Detalles Bibliográficos
Autores principales: Sun, Yuxi, Brimblecombe, Peter, Wei, Peng, Duan, Yusen, Pan, Jun, Liu, Qizhen, Fu, Qingyan, Peng, Zhiguang, Xu, Shuhong, Wang, Ying, Ning, Zhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416088/
https://www.ncbi.nlm.nih.gov/pubmed/36015765
http://dx.doi.org/10.3390/s22166005
Descripción
Sumario:Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide (NO(2)), and PM(2.5), which characterised spatial and temporal patterns of on-road pollutants. A total of 80% road coverage (motorways, trunk, primary, and secondary roads) required 80–100 taxis, but only 25 on trunk roads. Higher CO concentrations were observed in the urban centre, NO(2) higher in motorway concentrations, and PM(2.5) lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO(2), and PM(2.5) in Shanghai decreased by 32, 31 and 41%, compared with the previous period. Local contribution related to traffic emissions changed slightly before and after COVID-19 restrictions, while changing background contributions relate to seasonal variation. Mobile networks are a real-time tool for air quality monitoring, with high spatial resolution (~200 m) and robust against the loss of individual devices.