Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations

Author:

Bulot Florentin Michel Jacques12ORCID,Russell Hugo Savill3456ORCID,Rezaei Mohsen6,Johnson Matthew Stanley46ORCID,Ossont Steven James7ORCID,Morris Andrew Kevin Richard8ORCID,Basford Philip James1ORCID,Easton Natasha Hazel Celeste29ORCID,Mitchell Hazel Louise1ORCID,Foster Gavin Lee9ORCID,Loxham Matthew2101112ORCID,Cox Simon James12

Affiliation:

1. Faculty of Engineering and Physical Sciences, University of Southampton, Southampton SO17 1BJ, UK

2. Southampton Marine and Maritime Institute, University of Southampton, Southampton SO16 7QF, UK

3. Danish Big Data Centre for Environment and Health (BERTHA), Aarhus University, DK-4000 Roskilde, Denmark

4. AirScape UK, London W1U 6TQ, UK

5. Department of Environmental Science, Atmospheric Measurement, Aarhus University, DK-4000 Roskilde, Denmark

6. Department of Chemistry, University of Copenhagen, DK-2100 Copenhagen, Denmark

7. BizData, Melbourne, VIC 3000, Australia

8. National Oceanography Centre, Southampton SO14 3ZH, UK

9. School of Ocean and Earth Science, National Oceanography Centre, University of Southampton, Southampton SO14 3ZH, UK

10. Faculty of Medicine, University of Southampton, Southampton SO17 1BJ, UK

11. National Institute for Health Research, Southampton Biomedical Research Centre, Southampton SO16 6YD, UK

12. Institute for Life Sciences, University of Southampton, Southampton SO17 1BJ, UK

Abstract

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors’ to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Funder

Natural Environmental Research Council

Engineering and Physical Sciences Research Council

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

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