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

Yuxi SunPeter BrimblecombePeng WeiYusen DuanJun PanQizhen LiuQingyan FuZhiguang PengShuhong XuYing WangZhi Ning
Published in: Sensors (Basel, Switzerland) (2022)
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.
Keyphrases
  • air pollution
  • particulate matter
  • lung function
  • coronavirus disease
  • sars cov
  • high resolution
  • single molecule
  • healthcare
  • lower limb
  • chronic obstructive pulmonary disease