Source apportionment of fine atmospheric particles in Bloemfontein, South Africa, using positive matrix factorization
-
Published:2024-01-23
Issue:2
Volume:196
Page:
-
ISSN:0167-6369
-
Container-title:Environmental Monitoring and Assessment
-
language:en
-
Short-container-title:Environ Monit Assess
Author:
van der Westhuizen Deidré,Howlett-Downing Chantelle,Molnár Peter,Boman Johan,Wichmann Janine,von Eschwege Karel G.
Abstract
AbstractAir pollution is of major health and environmental concern globally and in South Africa. Studies on the sources of PM2.5 air pollution in low- and middle-income countries such as South Africa are limited. This study aimed to identify local and distant sources of PM2.5 pollution in Bloemfontein. PM2.5 samples were collected from June 16, 2020 to August 18, 2021. Trace element concentrations were determined by EDXRF spectroscopy. By use of the US EPA PMF 5.0 program, local sources were determined to be combustion/wood burning (49%), industry (22%), soil dust (10%), base metal/pyrometallurgical and traffic (9.6%) and water treatment/industry (9.4%). The HYSPLIT program was applied to determine distant PM2.5 source areas and the following clusters were identified: Mpumalanga province (52%), Northern Cape province (35%), Indian Ocean (8%) and Atlantic Ocean (6%). The majority of the air was found to come from the Mpumalanga province in the north-east, while the majority of local sources are ascribed to combustion/wood burning. Results from this study can be used to develop an Air Quality Management Plan for Bloemfontein.
Funder
South African National Research Foundation University of Gothenburg
Publisher
Springer Science and Business Media LLC
Reference50 articles.
1. Adeyemi, A., Molnar, P., Boman, J., & Wichmann, J. (2021). Source apportionment of fine atmospheric particles using positive matrix factorization in Pretoria. South Africa, Environ Monit Assess, 193, 716. https://doi.org/10.1007/s10661-021-09483-3 2. Adeyemi, A., Molnar, P., Boman, J., & Wichman, J. (2022). Archives of Environmental Contamination and Toxicology, 83(1), 77. https://doi.org/10.1007/s00244-022-00937-4 3. Almeida, A. M., et al. (2020). Ambient particulate matter source apportionment using receptor modelling in European and Central Asia urban areas. Environmental Pollution, 266, 115199. https://doi.org/10.1016/j.envpol.2020.115199 4. Bisht, D. S., Dumka, U. C., Kaskaoutis, D. G., Pipal, A. S., Srivastava, A. K., Soni, V. K., Attri, S. D., Sateesh, M., & Tiwari, S. (2015). Carbonaceous aerosols and pollutants over Delhi urban environment: Temporal evolution, source apportionment and radiative forcing. Science of the Total Environment, 521, 431–445. https://doi.org/10.1016/j.scitotenv.2015.03.083 5. Bond, T. C., Doherty, S. J., Fahey, D. W., Forster, P. M., Berntsen, T., DeAngelo, B. J., Flanner, M. G., Ghan, S., Karcher, B., Koch, D., & Kinne, S. (2013). Bounding the role of black carbon in the climate system: A scientific assessment. Journal of Geophysical Research Atmospheres, 118(11), 5380–5552. https://doi.org/10.1002/jgrd.50171
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|