Seasonal multisite low-cost sensor measurements to estimate spatial and temporal variability of particulate matter pollution in Nairobi, Kenya

Abstract

Ambient concentrations of fine particulate matter (PM_2.5) in sub-Saharan African cities like Nairobi can vary significantly due to the distribution and intensity of local and regional emission sources. We assess the spatiotemporal variability of PM_2.5 in Nairobi using low-cost sensor and reference instrument data from urban background (2020–2022) sites and from several source-specific sites (June to December 2021). To our knowledge, this work represents the longest and most spatially differentiated dataset for this city.

Data from urban background sites demonstrates seasonal variation driven by precipitation. PM_2.5 concentrations were higher during the warm-dry (JF, 17.1–18.8 μg m⁻³) and cool-dry (JJAS, 21.0–25.5 μg m⁻³) seasons and lower during the rainy seasons of MAM (14.8–17.0 μg m⁻³) and OND (13.2–17.2 μg m⁻³). Seasonal differences are systematic, and larger than the inter-annual variability. Our analysis of source-specific PM_2.5 measurements (June to December 2021) reveals for the more polluted JJAS season the highest PM_2.5 recorded at traffic/residential sites (28.8–29.1 μg m⁻³), followed by urban background (23.3–24.1 μg m⁻³) and sub-urban background (22.5 μg m⁻³). The traffic/residential impacted sites demonstrate noticeable morning and evening peaks associated with traffic and residential emissions, while diurnal profiles for urban background and sub-urban background sites remain flat during the day but display noticeable evening peaks, pointing again to the impact of residential emissions. At the urban background site and during the JJAS season, an additional midday peak is probably related to residential cooking emissions.