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

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations
Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations
Low-cost ParticulateMatter (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 PMsize 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.
air pollution, fine particles, laboratory study, low-cost sensors, particle number concentration, particulate matter
1424-8220
Bulot, Florentin
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Russell, Hugo
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Rezaei, Mohsen
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Johnson, Matthew Stanley
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Ossont, Steven James
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Morris, Andrew Kevin Richard
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Basford, Philip James
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Easton, Natasha Hazel Celeste
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Mitchell, Hazel Louise
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Foster, Gavin Lee
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Loxham, Matthew
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Cox, Simon James
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Bulot, Florentin
5ce5efd2-1bb7-4f55-a0de-c8cff4c152d8
Russell, Hugo
231283ca-2ebb-44dc-962a-232d35e951c3
Rezaei, Mohsen
4a1a15bb-7407-4fdb-954f-0e7414527069
Johnson, Matthew Stanley
48855c34-8f35-4d10-a6f6-69e9ace68362
Ossont, Steven James
6b903ec2-7bae-4a56-9c21-eea0a70bfa2b
Morris, Andrew Kevin Richard
00ef3bfb-219c-4ea7-86d2-dd4d71c083a6
Basford, Philip James
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Easton, Natasha Hazel Celeste
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Mitchell, Hazel Louise
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Foster, Gavin Lee
fbaa7255-7267-4443-a55e-e2a791213022
Loxham, Matthew
8ef02171-9040-4c1d-8452-2ca34c56facb
Cox, Simon James
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Bulot, Florentin, Russell, Hugo, Rezaei, Mohsen, Johnson, Matthew Stanley, Ossont, Steven James, Morris, Andrew Kevin Richard, Basford, Philip James, Easton, Natasha Hazel Celeste, Mitchell, Hazel Louise, Foster, Gavin Lee, Loxham, Matthew and Cox, Simon James (2023) Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations. Sensors, 23 (17), [7657]. (doi:10.3390/s23177657).

Record type: Article

Abstract

Low-cost ParticulateMatter (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 PMsize 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.

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Submitted date: 19 April 2023
Accepted/In Press date: 31 July 2023
Published date: 4 September 2023
Additional Information: Funding Information: This research was funded by the Next Generation of Unmanned Systems Centre for Doctoral Training supported by the Natural Environmental Research Council grant number [NE/N012070/1]; the Leverhulme Trust through the Southampton Marine and Maritime Institute; Engineering and Physical Sciences Research Council UK grant [EP/T517859/1]. Matthew Loxham is supported by a BBSRC David Phillips Fellowship [BB/V004573/1] and a NIHR Southampton Biomedical Research Centre Senior Fellowship. Hugo S. Russell was supported by Airscape, Aarhus University Graduate School of Science and Technology (GSST) and BERTHA—the Danish Big Data Centre for Environment and Health funded by the Novo Nordisk Foundation Challenge Programme (grant NNF17OC0027864). The test chamber at the University of Copenhagen is supported by ACTRIS-DK. The APC was funded by the Engineering and Physical Sciences Research Council. Publisher Copyright: © 2023 by the authors.
Keywords: air pollution, fine particles, laboratory study, low-cost sensors, particle number concentration, particulate matter

Identifiers

Local EPrints ID: 482723
URI: http://eprints.soton.ac.uk/id/eprint/482723
ISSN: 1424-8220
PURE UUID: 958ff7cd-d077-428b-bfe3-b88076f4cb46
ORCID for Steven James Ossont: ORCID iD orcid.org/0000-0003-3864-7072
ORCID for Philip James Basford: ORCID iD orcid.org/0000-0001-6058-8270
ORCID for Gavin Lee Foster: ORCID iD orcid.org/0000-0003-3688-9668
ORCID for Matthew Loxham: ORCID iD orcid.org/0000-0001-6459-538X

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Date deposited: 12 Oct 2023 16:33
Last modified: 18 Mar 2024 03:28

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Contributors

Author: Florentin Bulot
Author: Hugo Russell
Author: Mohsen Rezaei
Author: Matthew Stanley Johnson
Author: Andrew Kevin Richard Morris
Author: Natasha Hazel Celeste Easton
Author: Hazel Louise Mitchell
Author: Matthew Loxham ORCID iD
Author: Simon James Cox

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