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Citizen-operated mobile low-cost sensors for urban PM2.5 monitoring: field calibration, uncertainty estimation, and application
ORCID iD: 0000-0002-6470-0490
IVL Swedish Environmental Research Institute.
2023 (English)In: Sustainable cities and society, ISSN 2210-6707, Vol. 95, p. 104607-104607, article id 104607Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2023. Vol. 95, p. 104607-104607, article id 104607
Keywords [en]
Air quality monitoring; Particulate matters (PM2.5); Mobile low-cost sensors; Uncertainty analysis; Machine Learning; Snifferbike; Citizen science
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Environmental Sciences Meteorology and Atmospheric Sciences
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URN: urn:nbn:se:ivl:diva-4282DOI: 10.1016/j.scs.2023.104607Local ID: A2667OAI: oai:DiVA.org:ivl-4282DiVA, id: diva2:1823311
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NordForsk, 95326Available from: 2024-01-02 Created: 2024-01-02 Last updated: 2024-01-02

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Hassani, AmirhosseinWatne, Ågot K.
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Citation style
  • apa
  • harvard1
  • ieee
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More styles
Language
  • de-DE
  • en-GB
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Output format
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IVL Swedish Environmental Research Institute