Urban air quality management at low cost using micro air sensors: a case study from Accra, Ghana

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dc.contributor.authorHodoli, Collins Gameli
dc.contributor.authorMead, Iq
dc.contributor.authorCoulon, Frederic
dc.contributor.authorIvey, Cesunica E.
dc.contributor.authorTawiah, Victoria Owusu
dc.contributor.authorRaheja, Garima
dc.contributor.authorNimo, James
dc.contributor.authorHughes, Allison
dc.contributor.authorHaug, Achim
dc.contributor.authorKrause, Anika
dc.contributor.authorAmoah, Selina
dc.contributor.authorSunu, Maxwell
dc.contributor.authorNyante, John K.
dc.contributor.authorTetteh, Esi Nerquaye
dc.contributor.authorRiffault, Véronique
dc.contributor.authorMalings, Carl
dc.date.accessioned2024-12-19T15:43:57Z
dc.date.available2024-12-19T15:43:57Z
dc.date.freetoread2024-12-19
dc.date.issued2025-02-14
dc.date.pubOnline2024-11-06
dc.description.abstractUrban air quality management is dependent on the availability of local air pollution data. In many major urban centers of Africa, there is limited to nonexistent information on air quality. This is gradually changing in part due to the increasing use of micro air sensors, which have the potential to enable the generation of ground-based air quality data at fine scales for understanding local emission trends. Regional literature on the application of high-resolution data for emission source identification in this region is limited. In this study a micro air sensor was colocated at the Physics Department, University of Ghana, with a reference grade instrument to evaluate its performance for estimating PM2.5 pollution accurately at fine scales and the value of these data in identification of local sources and their behavior over time. For this study, 15 weeks of data at hourly resolution with approximately 2500 data pairs were generated and analyzed (June 1, 2023, to September 15, 2023). For this time period a coefficient of determination (r2) of 0.83 was generated with a mean absolute error (MAE) of 5.44 μg m–3 between the pre local calibration micro air sensor (i.e., out of the box) and the reference-grade instrument. Following currently accepted best practice methods (see, e.g., PAS4023) a domain specific (i.e., local) calibration factor was generated using a multilinear regression model, and when this factor is applied to the micro air sensor data, a reduction, i.e. improvement, in MAE to 1.43 μg m–3 was found. Daily variation was calculated, a receptor model was applied, and time series plots as a function of wind direction were generated, including PM2.5/PM10 ratio scatter and count plots, to explore the utility of this observational approach for local source identification. The 3 data sets were compared (out of the box, domain calibrated, and reference-grade) and it was found that although there were variations in the data reported, source areas highlighted based on these data were similar, with input from local sources such as traffic emissions and biomass burning. As the temporal resolution of observational data associated with these micro air sensors is higher than for reference grade instruments (primarily due to costs and logistics limitations), they have the potential to provide insight into the complex, often hyperlocalized sources associated with urban areas, such as those found in major African cities.
dc.description.journalNameACS ES&T Air
dc.description.sponsorshipUnited States Department of State, National Science Foundation, European Commission, Environmental Protection Agency
dc.description.sponsorshipThis work was unfunded. It is considered a contribution to knowledge from Clean Air One Atmosphere to support cleanair solutions in logistically difficult environments using science and micro air sensors based on result-oriented collaboration and team science. IMT Nord Europe acknowledges financial support from the Labex CaPPA project (ANR-11-LABX-0005-01), which is funded by the French National Research Agency(ANR) through the Programme d’Investissement d’Avenir(PIA), the Regional Council “Hauts-de-France”, and the European Regional Development Fund (ERDF).
dc.format.extentpp. 201-214
dc.identifier.citationHodoli CG, Mead I, Coulon F, et al., (2025) Urban air quality management at low cost using micro air sensors: a case study from Accra, Ghana. ACS ES&T Air, Volume 2, Issue 2, February 2025, pp. 201-214en_UK
dc.identifier.eissn2837-1402
dc.identifier.elementsID558560
dc.identifier.issn2837-1402
dc.identifier.issueNo2
dc.identifier.urihttps://doi.org/10.1021/acsestair.4c00172
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/23277
dc.identifier.volumeNo2
dc.languageEnglish
dc.language.isoen
dc.publisherAmerican Chemical Society en_UK
dc.publisher.urihttps://pubs.acs.org/doi/10.1021/acsestair.4c00172#
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject37 Earth Sciencesen_UK
dc.subject3701 Atmospheric Sciencesen_UK
dc.subject41 Environmental Sciencesen_UK
dc.subject4105 Pollution and Contaminationen_UK
dc.subject11 Sustainable Cities and Communitiesen_UK
dc.titleUrban air quality management at low cost using micro air sensors: a case study from Accra, Ghanaen_UK
dc.typeArticle
dcterms.dateAccepted2024-10-25

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