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 (NO2), and PM2.5, 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, NO2 higher in motorway concentrations, and PM2.5 lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO2, and PM2.5 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 (similar to 200 m) and robust against the loss of individual devices.

Automated summary

This study monitored traffic-related air pollution in Shanghai using a mobile sensor network on urban taxis. The results showed spatial and temporal patterns of pollutants, with higher CO concentrations in the urban centre, higher NO2 concentrations on motorways, and lower PM2.5 concentrations in the west. During the COVID-19 lockdown, there was a significant decrease in CO, NO2, and PM2.5 concentrations. The study also found that traffic emissions had a slightly different contribution to air pollution before and after the COVID-19 restrictions, while background contributions varied with seasonal changes.