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

Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment
Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment
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 ~1 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.This dataset contains: 1. sensor_data.Rds (R format) containing the data from the sensors averaged (median) per minute over the period of the study (13/03/18 until 28/02/19) 2. winddata.csv containing the data from the meteorological station over the period of the study (13/03/18 until 28/02/19) taken from http://www.southamptonweather.co.uk/ 3. CV_for_ICC.csv containing the coefficients of variation calculated and used for the Intra Class Correlation (ICC) analysis 4. Figure5.zip (zip file) containing the CSV files underlying the data presented in Figure 5 of the paper and underlying Supplementary Figure S15: - Figure 5: - - month.csv: correlation per month with the background reference station per sensor per AQM - - NoAugust.BG.csv: correlation per quartiles of background PM25 concentrations per sensor per AQM excluding August 2018 - - NoAugust.RH.csv: correlation per quartiles of relative humidity per sensor per AQM excluding August 2018 - - NoAugust.Temperature.csv: correlation per quartiles of temperature per sensor per AQM excluding August 2018 - - NoAugust.wd.csv: correlation per wind direction per sensor per AQM excluding August 2018 - Supplementary Figure S15: - - BG.csv: correlation per quartiles of background PM25 concentrations per sensor per AQM - - RH.csv: correlation per quartiles of relative humidity per sensor per AQM - - Temperature.csv: correlation per quartiles of temperature per sensor per AQM - - wd.csv: correlation per wind direction per sensor per AQM
Zenodo
Bulot, Florentin
47870de2-3ba2-4425-b07a-16ce48ee3956
Johnston, Steven
6b903ec2-7bae-4a56-9c21-eea0a70bfa2b
Basford, Philip J
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Easton, Natasha, Hazel Celeste
56583bc7-b005-40d8-8571-99d335430a8f
Cox, Simon
0e62aaed-24ad-4a74-b996-f606e40e5c55
Foster, Gavin
fbaa7255-7267-4443-a55e-e2a791213022
Morris, Andrew K.
0d154ca5-f00a-4eb8-a2b2-1a6e581bf7f1
Apetroia-Cristea;, Mihaela
786c8bcf-b9ac-402d-a370-ee28ce2da26e
Loxham, Matthew
8ef02171-9040-4c1d-8452-2ca34c56facb
Bulot, Florentin
47870de2-3ba2-4425-b07a-16ce48ee3956
Johnston, Steven
6b903ec2-7bae-4a56-9c21-eea0a70bfa2b
Basford, Philip J
efd8fbec-4a5f-4914-bf29-885b7f4677a7
Easton, Natasha, Hazel Celeste
56583bc7-b005-40d8-8571-99d335430a8f
Cox, Simon
0e62aaed-24ad-4a74-b996-f606e40e5c55
Foster, Gavin
fbaa7255-7267-4443-a55e-e2a791213022
Morris, Andrew K.
0d154ca5-f00a-4eb8-a2b2-1a6e581bf7f1
Apetroia-Cristea;, Mihaela
786c8bcf-b9ac-402d-a370-ee28ce2da26e
Loxham, Matthew
8ef02171-9040-4c1d-8452-2ca34c56facb

Bulot, Florentin, Johnston, Steven, Basford, Philip J, Easton, Natasha, Hazel Celeste, Cox, Simon, Foster, Gavin, Morris, Andrew K., Apetroia-Cristea;, Mihaela and Loxham, Matthew (2019) Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment. Zenodo doi:10.5281/zenodo.2605402 [Dataset]

Record type: Dataset

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 ~1 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.This dataset contains: 1. sensor_data.Rds (R format) containing the data from the sensors averaged (median) per minute over the period of the study (13/03/18 until 28/02/19) 2. winddata.csv containing the data from the meteorological station over the period of the study (13/03/18 until 28/02/19) taken from http://www.southamptonweather.co.uk/ 3. CV_for_ICC.csv containing the coefficients of variation calculated and used for the Intra Class Correlation (ICC) analysis 4. Figure5.zip (zip file) containing the CSV files underlying the data presented in Figure 5 of the paper and underlying Supplementary Figure S15: - Figure 5: - - month.csv: correlation per month with the background reference station per sensor per AQM - - NoAugust.BG.csv: correlation per quartiles of background PM25 concentrations per sensor per AQM excluding August 2018 - - NoAugust.RH.csv: correlation per quartiles of relative humidity per sensor per AQM excluding August 2018 - - NoAugust.Temperature.csv: correlation per quartiles of temperature per sensor per AQM excluding August 2018 - - NoAugust.wd.csv: correlation per wind direction per sensor per AQM excluding August 2018 - Supplementary Figure S15: - - BG.csv: correlation per quartiles of background PM25 concentrations per sensor per AQM - - RH.csv: correlation per quartiles of relative humidity per sensor per AQM - - Temperature.csv: correlation per quartiles of temperature per sensor per AQM - - wd.csv: correlation per wind direction per sensor per AQM

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Published date: 15 May 2019

Identifiers

Local EPrints ID: 431866
URI: https://eprints.soton.ac.uk/id/eprint/431866
PURE UUID: 8e83764d-bc67-46f9-96c7-78a4066f077b
ORCID for Steven Johnston: ORCID iD orcid.org/0000-0003-3864-7072
ORCID for Philip J Basford: ORCID iD orcid.org/0000-0001-6058-8270
ORCID for Gavin 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: 19 Jun 2019 16:32
Last modified: 20 Jun 2019 00:35

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Contributors

Creator: Florentin Bulot
Creator: Steven Johnston ORCID iD
Creator: Philip J Basford ORCID iD
Creator: Natasha, Hazel Celeste Easton
Creator: Simon Cox
Creator: Gavin Foster ORCID iD
Creator: Andrew K. Morris
Creator: Mihaela Apetroia-Cristea;
Creator: Matthew Loxham ORCID iD

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