Skip to main navigation Skip to search Skip to main content

Spatiotemporal Assessment of PM2.5 in Senior High Schools in Kumasi, Ghana using Low-Cost Sensors

  • Victoria Owusu-Tawiah
  • , Thompson Annor
  • , Edmund I. Yamba
  • , James Nimo
  • , Cosmos Senyo Wemegah
  • , Collins Gameli Hodoli
  • , Desmond Osei-Tutu
  • , Daniel Amponsah
  • , Allison Felix Hughes
  • , Daniel M. Westervelt
  • Kwame Nkrumah University of Science and Technology
  • Kigali Collaborative Research Centre
  • State University of New York Albany
  • Univ. of Energy and Natural Resources
  • Clean Air One Atmosphere
  • Columbia University

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Abstract: Fine particulate matter (PM2.5) poses significant health risks, particularly to children; yet, ambient air quality studies in school environments across Kumasi, Ghana, remain limited. This study utilized low-cost Airnote sensors and meteorological data (wind speed and wind direction) from the ERA5-Land Reanalysis to assess levels of PM2.5 pollution across six senior high schools in Kumasi between 2022 and 2023, capturing spatial and seasonal variability during both the dry and wet seasons. Results revealed an annual median PM2.5 concentration of 17.18 μg/m3, exceeding the WHO annual guideline of 5 μg/m3. Diurnal patterns exhibited bimodal peaks aligned with morning and evening commuting and domestic activities, driven by traffic emissions, biomass burning, and informal waste burning. Pollution levels were notably elevated during weekdays and Saturdays but lower on Sundays. Median concentrations were highest at SHS E (20.91 μg/m3), followed by SHS A (19.22 μg/m3), SHS F (18.16 μg/m3), and SHS D (16.71 μg/m3), while SHS B (15.32 μg/m3) and SHS C (12.76 μg/m3) recorded the lowest levels. Seasonal differences were pronounced: the dry season showed significantly higher pollution (mean = 26.82 μg/m3) than the wet season (mean = 13.18 μg/m3), owing to reduced rainfall and limited atmospheric dispersion. Conditional Bivariate Probability Function (CBPF) analysis and HYSPLIT back-trajectory modeling identified dominant pollution sources, including nearby traffic corridors, domestic combustion activities, unmanaged waste burning, and long-range Saharan dust transport, with clear seasonal shifts in source directionality. Spatial variability in PM2.5 concentrations was further influenced by land-use characteristics and topography surrounding each school. These findings underscore the need for localized air quality management strategies, particularly in vulnerable environments like schools, to mitigate health risks and enhance urban air quality governance. Graphic Abstract: (Figure presented.)

Original languageEnglish
Article number66
JournalAerosol and Air Quality Research
Volume25
Issue number12
DOIs
Publication statusPublished - Dec 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being
  2. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities
  3. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Assessment
  • Ghana
  • Kumasi
  • PM
  • School
  • Senior high
  • Source attribution
  • Spatiotemporal

Fingerprint

Dive into the research topics of 'Spatiotemporal Assessment of PM2.5 in Senior High Schools in Kumasi, Ghana using Low-Cost Sensors'. Together they form a unique fingerprint.

Cite this