Articles | Volume 14, issue 18
Atmos. Chem. Phys., 14, 9977–9991, 2014
Atmos. Chem. Phys., 14, 9977–9991, 2014

Research article 19 Sep 2014

Research article | 19 Sep 2014

Source apportionment and seasonal variation of PM2.5 in a Sub-Saharan African city: Nairobi, Kenya

S. M. Gaita1, J. Boman1, M. J. Gatari2, J. B. C. Pettersson1, and S. Janhäll3 S. M. Gaita et al.
  • 1Department of Chemistry and Molecular Biology, Atmospheric Science, University of Gothenburg, 412 96 Gothenburg, Sweden
  • 2Institute of Nuclear Science and Technology, University of Nairobi, P.O. Box 30197, 00100 Nairobi, Kenya
  • 3VTI – Swedish National Road and Transport Research Institute, P.O. Box 8072, 402 78 Gothenburg, Sweden

Abstract. Sources of airborne particulate matter and their seasonal variation in urban areas in Sub-Saharan Africa are poorly understood due to lack of long-term measurement data. In view of this, filter samples of airborne particulate matter (particle diameter ≤2.5 μm, PM2.5) were collected between May 2008 and April 2010 at two sites (urban background site and suburban site) within the Nairobi metropolitan area. A total of 780 samples were collected and analyzed for particulate mass, black carbon (BC) and 13 trace elements. The average PM2.5 concentration at the urban background site was 21±9.5 μg m−3, whereas the concentration at the suburban site was 13±7.3 μg m−3. The daily PM2.5 concentrations exceeded 25 μg m−3 (the World Health Organization 24 h guideline value) on 29% of the days at the urban background site and 7% of the days at the suburban site. At both sites, BC, Fe, S and Cl accounted for approximately 80% of all detected elements. Positive matrix factorization analysis identified five source factors that contribute to PM2.5 in Nairobi, namely traffic, mineral dust, industry, combustion and a mixed factor (composed of biomass burning, secondary aerosol and aged sea salt). Mineral dust and traffic factors were related to approximately 74% of PM2.5. The identified source factors exhibited seasonal variation, apart from the traffic factor, which was prominently consistent throughout the sampling period. Weekly variations were observed in all factors, with weekdays having higher concentrations than weekends. The results provide information that can be exploited for policy formulation and mitigation strategies to control air pollution in Sub-Saharan African cities.

Final-revised paper