TY - JOUR

T1 - Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution—Part B—Particle Number Concentrations

AU - Bulot, Florentin Michel Jacques

AU - Russell, Hugo Savill

AU - Rezaei, Mohsen

AU - Johnson, Matthew Stanley

AU - Ossont, Steven James

AU - Morris, Andrew Kevin Richard

AU - Basford, Philip James

AU - Easton, Natasha Hazel Celeste

AU - Mitchell, Hazel Louise

AU - Foster, Gavin Lee

AU - Loxham, Matthew

AU - Cox, Simon James

N1 - 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.

PY - 2023/9

Y1 - 2023/9

N2 - 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.

AB - 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.

KW - air pollution

KW - fine particles

KW - laboratory study

KW - low-cost sensors

KW - particle number concentration

KW - particulate matter

U2 - 10.3390/s23177657

DO - 10.3390/s23177657

M3 - Journal article

C2 - 37688113

AN - SCOPUS:85170345425

VL - 23

JO - Sensors

JF - Sensors

SN - 1424-3210

IS - 17

M1 - 7657

ER -