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

Ambient concentrations of 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 an urban background (2020 – 2022) site 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 the urban background site 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. • Assessment of the spatiotemporal variability of fine particle concentrations (PM 2.5 ) in Nairobi using low-cost sensor and reference instrument observations • Three year long (2020 – 2022) hourly PM 2.5 measurements at urban background sites • 7 months long PM 2.5 observations (June to December 2021) at seven urban background and source specific sites in the Nairobi area. • Diurnal variations pointing to residential (cooking) and traffic emissions.

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Publication Details

Journal
Atmospheric Pollution Research
Published
2025-06-18
DOI
https://doi.org/10.1016/j.apr.2025.102630
Citations
2
Primary Topic
Air Quality Monitoring and Forecasting
Type
article
Field-Weighted Citation Impact
1.60

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article

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

Michael Gatari, John Mungai, V. Faye McNeill, Matthias Beekmann et al.
2 citations
Atmospheric Pollution Research
Air Quality Monitoring and Forecasting
1.60
article

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

Michael Gatari, John Mungai, V. Faye McNeill, Matthias Beekmann, Godwin Opinde, Michael R. Giordano, Daniel M. Westervelt, Ezekiel Waiguru Nyaga, Albert A. Presto, R. Subramanian, Emilia Tjernström
article en
2 citations

Abstract

Ambient concentrations of 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 an urban background (2020 – 2022) site 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 the urban background site 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. • Assessment of the spatiotemporal variability of fine particle concentrations (PM 2.5 ) in Nairobi using low-cost sensor and reference instrument observations • Three year long (2020 – 2022) hourly PM 2.5 measurements at urban background sites • 7 months long PM 2.5 observations (June to December 2021) at seven urban background and source specific sites in the Nairobi area. • Diurnal variations pointing to residential (cooking) and traffic emissions.

Atmospheric Pollution ResearchVol. 16(10)
University of Nairobi (KE), Centre National de la Recherche Scientifique (FR), Lamont-Doherty Earth Observatory (US), Kenyatta University (KE), Université Paris-Est Créteil (FR), Université Paris Cité (FR), Paris-Est Sup (FR), Practical Action (KE), Université Mohammed VI Polytechnique (MA), Laboratoire Interuniversitaire des Systèmes Atmosphériques (FR), Laboratoire Techniques, Territoires et Sociétés (FR), Monash University (AU), Carnegie Mellon University (US), Columbia University (US)
Carnegie Mellon University, Newton Fund, University of Leicester, Agence Nationale de la Recherche, Université de Paris
Climate action
Openalex Percentile: Top 17%
Air Quality Monitoring and Forecasting
1.60
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