Monitoring Excess Exposure to Air Pollution for Professional Drivers in London Using Low-Cost Sensors

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DOI

  • Louise Bøge Frederickson
  • Shanon Lim, Imperial College London
  • ,
  • Hugo Savill Russell
  • Szymon Kwiatkowski, AirLabs Denmark
  • ,
  • James Bonomaully, AirLabs Denmark
  • ,
  • Johan Albrecht Schmidt, AirLabs Denmark
  • ,
  • Ole Hertel
  • Ian Mudway, Imperial College London
  • ,
  • Benjamin Barratt, Imperial College London
  • ,
  • Matthew S. Johnson, University of Copenhagen, AirLabs Denmark, Denmark
In this pilot study, low-cost air pollution sensor nodes were fitted in waste removal trucks, hospital vans and taxis to record drivers’ exposure to air pollution in Central London. Particulate matter (PM2.5 and PM10 ), CO2 , NO2 , temperature and humidity were recorded in real-time with nodes containing low-cost sensors, an electrochemical gas sensor for NO 2 , an optical particle counter for PM2.5 and PM10 and a non-dispersive infrared (NDIR) sensor for CO2 , temperature and relative humidity. An intervention using a pollution filter to trap PM and NO 2 was also evaluated. The measurements were compared with urban background and roadside monitoring stations at Honor Oak Park and Marylebone Road, respectively. The vehicle records show PM and NO2 concentrations similar to Marylebone Road and a higher NO2 -to-PM ratio than at Honor Oak Park. Drivers are exposed to elevated pollution levels relative to Honor Oak Park: 1.72 μg m−3 , 1.92 μg m−3 and 58.38 ppb for PM2.5 , PM10 , and NO2 , respectively. The CO2 levels ranged from 410 to over 4000 ppm. There is a significant difference in average concentrations of PM2.5 and PM10 between the vehicle types and a non-significant difference in the average concentrations measured with and without the pollution filter within the sectors. In conclusion, drivers face elevated air pollution exposure as part of their jobs.
Original languageEnglish
Article number749
JournalAtmosphere
Volume11
Issue7
Number of pages18
DOIs
Publication statusPublished - 2020

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