Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

Florentin M J Bulot,Simon J Cox,Andrew K R Morris,Steven J Johnston,Gavin L Foster,Mihaela Apetroaie-Cristea,Philip J Basford,Natasha H C Easton,Matthew Loxham

doi:10.1038/s41598-019-43716-3

Abstract

Exposure to ambient particulate matter (PM) air pollution is a leading risk factor for morbidity and mortality, associated with up to 8.9 million deaths/year worldwide. Measurement of personal exposure to PM is hindered by poor spatial resolution of monitoring networks. Low-cost PM sensors may improve monitoring resolution in a cost-effective manner but there are doubts regarding data reliability. PM sensor boxes were constructed using four low-cost PM micro-sensor models. Three boxes were deployed at each of two schools in Southampton, UK, for around one year and sensor performance was analysed. Comparison of sensor readings with a nearby background station showed moderate to good correlation (0.61 < r < 0.88, p < 0.0001), but indicated that low-cost sensor performance varies with different PM sources and background concentrations, and to a lesser extent relative humidity and temperature. This may have implications for their potential use in different locations. Data also indicates that these sensors can track short-lived events of pollution, especially in conjunction with wind data. We conclude that, with appropriate consideration of potential confounding factors, low-cost PM sensors may be suitable for PM monitoring where reference-standard equipment is not available or feasible, and that they may be useful in studying spatially localised airborne PM concentrations.

Highlights

Background concentrationAll sensors showed increasing correlation with the background station as background pollution increased with Pearson coefficients >0.6 for the Plantowers and >0.4 for the Alphasense OPC-N2 for background pollution in the upper quartile (17.8 to 77.4 μg/m3)
An error occured configuring the Honeywell HPMA115S0 (a 5 V logic was used instead of a 3.3 V logic) which could only be fixed for Air Quality Monitor (AQM) A.1 due to limited resources and access restrictions
For AQM B.2, the Alphasense OPC-N2 experienced intermittent communication issues falling into categories 1 and 2 of the data quality check process from 13/03/18 until 21/06/18 and from 13/09/18 until 19/11/18

Summary

Introduction

All sensors showed increasing correlation with the background station as background pollution increased with Pearson coefficients >0.6 for the Plantowers and >0.4 for the Alphasense OPC-N2 for background pollution in the upper quartile (17.8 to 77.4 μg/m3). For the 3 sensors, the second background PM2.5 quartile showed a significantly lower Pearson correlation than the highest group. The two Plantower sensors presented a better correlation with the background PM2.5 station at the upper quartiles of relative humidity (76–98% RH). For the Alphasense OPC-N2, there was no significant difference between the different quartiles while the correlation dropped for the third quartile. At lower relative humidity there is more variability across the sites illustrated by the spread of the boxes with the Alphasense OPC-N2 presenting the widest range of values. The two Plantower sensors present significant differences between their upper quartile and their first and second quartiles

Objectives

Methods

Results

Discussion

Conclusion