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First long-term air quality assessment in Luanda, Angola: Performance evaluation of a low-cost monitoring station against reference equipment

2026Artigo científico Acesso aberto
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datacite.subject.fosCiências Naturais::Ciências da Terra e do Ambiente
datacite.subject.fosEngenharia e Tecnologia::Engenharia do Ambiente
datacite.subject.sdg03:Saúde de Qualidade
datacite.subject.sdg11:Cidades e Comunidades Sustentáveis
datacite.subject.sdg13:Ação Climática
dc.contributor.authorSilva, Alan Victor da
dc.contributor.authorFurst, Leonardo
dc.contributor.authorCipoli, Yago A.
dc.contributor.authorSoares, Marlene J.S.
dc.contributor.authorLeitão, Anabela G.A.
dc.contributor.authorFeliciano, Manuel
dc.contributor.authorAlves, Célia A.
dc.date.accessioned2026-02-16T14:14:20Z
dc.date.available2026-02-16T14:14:20Z
dc.date.issued2026
dc.description.abstractLow-cost air quality monitoring stations (LCMS), which integrate sensors for gases and particulate matter (PM), offer an economical solution for expanding monitoring networks. However, their reliability requires validation, particularly in rapidly urbanising regions with limited infrastructure. This study presents the first long-term, continuous, multi-pollutant air quality assessment in Luanda, Angola - where no monitoring stations currently exist - by evaluating the performance of an LCMS against reference-grade equipment. Daily averages, correlation metrics (R-2, RMSE), and a hybrid Bland-Altman/regression analyses were used to evaluate the agreement. Results indicated strong correlation for CO (R-2 = 0.96; RMSE = 0.24 ppm) and good for NO2 (R-2 = 0.81; RMSE = 6.35 ppb), although limitations near detection limits were noted. Significant challenges were identified in O-3 measurements (R-2 = 0.77, RMSE = 7.13 ppb), primarily due to strong cross-sensitivity to high ambient NO2 levels and potential sensor ageing. For PM10 and PM2.5, although good linear correlations (R-2 similar to 0.82) were observed with reference methods, the LCMS exhibited considerable systematic bias (RMSE over 46 mu g/m(-3)) and consistently underestimate concentrations. The study also registered frequent and severe exceedances of WHO AQG and EU standards for PM10, PM2.5, and NO2, underscoring significant public health risks. Despite limitations, particularly for O-3 measurements and biases in PM data, the LCMS demonstrates potential as a cost-effective tool to complement reference networks, enhance spatial monitoring coverage, identify pollution hotspots, and support air quality management in resource-constrained settings, since continuous calibration and validation procedures are implemented to mitigate measurement uncertainties.eng
dc.description.sponsorshipThis work was supported by the Portuguese Foundation for Science and Technology (FCT) through the PhD fellowships 2023.02059.BD, 2023.04826.BD, SFRH/BD/04992/2021 and SRFH/BD/08461/2020. The research was performed in the frame of the project APAM, financially supported by national funds (OE), through FCT/MCTES (DOI: 10.54499/2022.04240.PTDC). This work was also financed by national funds through FCT under the project/grant UID/50006 + LA/P/0094/2020 (doi.org/10.54499/LA/P/0094/2020), and through FCT/MCTES (PIDDAC): CIMO, UIDB/00690/2020 (DOI: 10.54499/UIDB/00690/2020); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020). We would also like to sincerely thank d·nota® and bettair® for providing the equipment used in our tests. Additionally, we would like to thank the Faculty of Engineering of the Agostinho Neto University for providing the logistical conditions for carrying out the monitoring campaign in Luanda.
dc.identifier.citationDa Silva, Alan V.; Furst, Leonardo; Cipoli, Yago A.; Soares, Marlene J. S.; Leitao, Anabela G. A.; Feliciano, Manuel; Alves, Celia A. (2026). First long-term air quality assessment in Luanda, Angola: Performance evaluation of a low-cost monitoring station against reference equipment. Atmospheric Pollution Research. ISSN 1309-1042. 17:2, p. 1-13
dc.identifier.doi10.1016/j.apr.2025.102746
dc.identifier.issn1309-1042
dc.identifier.urihttp://hdl.handle.net/10198/35758
dc.language.isoeng
dc.peerreviewedyes
dc.publisherElsevier
dc.relationMountain Research Center
dc.relationAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
dc.relation.ispartofAtmospheric Pollution Research
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/
dc.subjectLow-cost sensors
dc.subjectOptical methods
dc.subjectBeta attenuation monitor
dc.subjectGravimetric methods
dc.subjectLuanda
dc.titleFirst long-term air quality assessment in Luanda, Angola: Performance evaluation of a low-cost monitoring station against reference equipmenteng
dc.typejournal article
dspace.entity.typePublication
oaire.awardNumberUIDB/00690/2020
oaire.awardNumberLA/P/0007/2020
oaire.awardTitleMountain Research Center
oaire.awardTitleAssociate Laboratory for Sustainability and Tecnology in Mountain Regions
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00690%2F2020/PT
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT
oaire.citation.endPage13
oaire.citation.issue2
oaire.citation.startPage1
oaire.citation.titleAtmospheric Pollution Research
oaire.citation.volume17
oaire.fundingStream6817 - DCRRNI ID
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFeliciano
person.givenNameManuel
person.identifier.ciencia-id2D11-7230-702B
person.identifier.orcid0000-0002-3147-4511
person.identifier.scopus-author-id6603358480
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
project.funder.nameFundação para a Ciência e a Tecnologia
relation.isAuthorOfPublicationccb9c69d-2820-493b-ab44-77b0538814fa
relation.isAuthorOfPublication.latestForDiscoveryccb9c69d-2820-493b-ab44-77b0538814fa
relation.isProjectOfPublication29718e93-4989-42bb-bcbc-4daff3870b25
relation.isProjectOfPublication6255046e-bc79-4b82-8884-8b52074b4384
relation.isProjectOfPublication.latestForDiscovery29718e93-4989-42bb-bcbc-4daff3870b25

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