preprint
<title>Abstract</title> noindent Fine particulate matter (PM\textsubscript{2.5}) 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 PM\textsubscript{2.5} 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 PM\textsubscript{2.5} concentration of 17.18 \(\mu\)g/m\(^3\), exceeding the WHO annual guideline of 5 $\mu$g/m$^3$. 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 OKESS (20.91 $\mu$g/m$^3$), followed by Adventist (19.22 $\mu$g/m$^3$), Sakafia (18.16 $\mu$g/m$^3$), and KWG (16.71 $\mu$g/m$^3$), while Ibadur (15.32 $\mu$g/m$^3$) and KASS (12.76 $\mu$g/m$^3$) recorded the lowest levels. Seasonal differences were pronounced: the dry season showed significantly higher pollution (mean = 26.82 $\mu$g/m$^3$) than the wet season (mean = 13.18 $\mu$g/m$^3$), 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 PM\textsubscript{2.5} 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.
This page summarises published work. The authoritative version sits with the publisher.
DOI: 10.21203/rs.3.rs-6941594/v1
Is something wrong with this record? Report it or request removal.
Discussion
Have you built on this work, tried to replicate it, or seen it applied in practice? Share what you know. Verified researchers and MARATTO™ domain experts can open a discussion, and any member can reply. Contributions are reviewed before they appear.
No discussion yet. Open the first thread.
New to MARATTO™? Create a free account.