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

Louise Bøge Frederickson,Benjamin Barratt,Johan Albrecht Schmidt,Shanon Lim,Ole Hertel,James Bonomaully,Hugo Savill Russell,Szymon Kwiatkowski,Matthew Stanley Johnson,Ian Mudway

doi:10.3390/atmos11070749

Louise Bøge Frederickson, Benjamin Barratt + Show 8 more

Open Access

https://doi.org/10.3390/atmos11070749

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Abstract

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 (PM 2.5 and PM 10 ), CO 2 , NO 2 , 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 PM 2.5 and PM 10 and a non-dispersive infrared (NDIR) sensor for CO 2 , 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 NO 2 concentrations similar to Marylebone Road and a higher NO 2 -to-PM ratio than at Honor Oak Park. Drivers are exposed to elevated pollution levels relative to Honor Oak Park: 1.72 μ g m − 3 , 1.92 μ g m − 3 and 58.38 ppb for PM 2.5 , PM 10 , and NO 2 , respectively. The CO 2 levels ranged from 410 to over 4000 ppm. There is a significant difference in average concentrations of PM 2.5 and PM 10 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.

Highlights

Traffic-related air pollution has a disproportionate local effect on passengers and drivers, cyclists and pedestrians and residents in areas with a high traffic density [1]
Data from six of the days were excluded because the time series were interrupted due to technical problems, the disruption of communication or AirNode Generation One (AGO) handling errors
The data show substantial variability in in-cabin concentrations of all pollutants between sectors, drivers and times and locations, which is due to the changes in traffic density, air exchange rate, meteorology, vehicle operational mode and the air quality of the driving area

Summary

Introduction

Traffic-related air pollution has a disproportionate local effect on passengers and drivers, cyclists and pedestrians and residents in areas with a high traffic density [1]. Several studies have shown that air pollution exposure is higher for people inside a vehicle cabin than for cyclists or pedestrians outside, within or near high traffic locations [8,9,10,11,12]. While most people only commute one to two hours per day, it is likely that those that are required to work in this environment are disproportionately affected by high air pollution exposure [13,14]

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