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Source apportionment of fine atmospheric particles using positive matrix factorization in Pretoria, South Africa

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Abstract

In Pretoria South Africa, we looked into the origins of fine particulate matter (PM2.5), based on 1-year sampling campaign carried out between April 18, 2017, and April 17, 2018. The average PM2.5 concentration was 21.1 ± 15.0 µg/m3 (range 0.7–66.8 µg/m3), with winter being the highest and summer being the lowest. The XEPOS 5 energy dispersive X-ray fluorescence (EDXRF) spectroscopy was used for elemental analysis, and the US EPA PMF 5.0 program was used for source apportionment. The sources identified include fossil fuel combustion, soil dust, secondary sulphur, vehicle exhaust, road traffic, base metal/pyrometallurgical, and coal burning. Coal burning and secondary sulphur were significantly higher in winter and contributed more than 50% of PM2.5 sources. The HYSPLIT model was used to calculate the air mass trajectories (version 4.9). During the 1-year research cycle, five transportation clusters were established: North Limpopo (NLP), Eastern Inland (EI), Short-Indian Ocean (SIO), Long-Indian Ocean (LIO), and South Westerly-Atlantic Ocean (SWA). Local and transboundary origin accounted for 85%, while 15% were long-range transport. Due to various anthropogenic activities such as biomass burning and coal mining, NLP clusters were the key source of emissions adding to the city’s PM rate. In Pretoria, the main possible source regions of PM2.5 were discovered to be NLP and EI. Effective control strategies designed at reducing secondary sulphur, coal burning, and fossil fuel combustion emissions at Southern African level and local combustion sources would be an important measure to combat the reduction of ambient PM2.5 pollution in Pretoria.

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Availability of data and material

The datasets generated and/or analyzed during the current study are not publicly available due to university’s intellectual property right but are available from the corresponding author on reasonable request.

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Acknowledgements

The authors gratefully acknowledge the NOAA Air Resources Laboratory for providing the HYSPLIT model and the NCEP Reanalysis datasets, as well as the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA. The authors would like to thank the South African Weather Service for the air pollution and meteorological data, University of Pretoria, and the National Research Foundation for the doctoral scholarship of A.A.A.

Funding

JW received funding from the South African National Research Foundation under the Collaborative Postgraduate Training Programme grant (CPT160424162937).

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Authors and Affiliations

  1. School of Health Systems and Public Health, University of Pretoria, 31 Bophelo Road 00 01, Pretoria, South Africa

    Adewale Adeyemi & Janine Wichmann

  2. Department of Environmental Modeling and Biometrics, Forestry Research Institute of Nigeria, Ibadan, Nigeria

    Adewale Adeyemi

  3. Occupational and Environmental Medicine, Sahlgrenska University Hospital & University of Gothenburg, Medicinaregatan 16A, 40530, Gothenburg, Sweden

    Peter Molnar

  4. Department of Chemistry and Molecular Biology, University of Gothenburg Sweden, Gothenburg, Sweden

    Johan Boman

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  1. Adewale Adeyemi
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  2. Peter Molnar
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  3. Johan Boman
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  4. Janine Wichmann
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Contributions

JW conceptualized the research. The research design, methodology, analysis of findings, and writing of the manuscript were all the responsibility of the authors. The statistical analyses were carried out by AA and PM. JB was responsible for the chemical analysis. The authors read and approved the final manuscript.

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Correspondence to Adewale Adeyemi.

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The Research Ethics Committee, Faculty of Health Sciences, University of Pretoria, approved ethics approval (reference 469/2017) in 2017.

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The authors declare that they have no conflict of interest.

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Adeyemi, A., Molnar, P., Boman, J. et al. Source apportionment of fine atmospheric particles using positive matrix factorization in Pretoria, South Africa. Environ Monit Assess 193, 716 (2021). https://doi.org/10.1007/s10661-021-09483-3

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