DN-PMF as a sensitivity test for conventional PMF (C-PMF) source apportionment in three cities in South Africa, 2017–2018
| dc.contributor.author | Howlett-Downing, Chantelle Margaret | |
| dc.contributor.author | Boman, Johan | |
| dc.contributor.author | Molnar, Peter | |
| dc.contributor.author | Wichmann, Janine | |
| dc.contributor.email | chantelle.howlett-downing@mrc.ac.za | |
| dc.date.accessioned | 2026-03-16T10:46:41Z | |
| dc.date.available | 2026-03-16T10:46:41Z | |
| dc.date.issued | 2026 | |
| dc.description.abstract | Source apportionment through factorization is a common method for identifying sources of air pollution. Both PCA and DN-PMF have assumptions, strengths, and limitations. Assigning sources to factors is inherently subjective and can introduce bias. PCA for the number of sources, C-PMF and DN-PMF is performed on data from three cities which were sampled at the same time, 16 April 2017 to 18 April 2018. The DN-PMF was able to give seasonal information to support the source apportionment. Results of the PCA included 6 factors for Thohoyandou and Pretoria and 7 factors for Cape Town. At the two large city sites, the C-PMF presented a dominant coal emissions source (29% and 35.6%) yearly and a strong biomass source during winter (24% and 17%). The dominant yearly source shifted to vehicular emissions with the DN-PMF model in Pretoria and Cape Town (41% and 12%) and coal burning at Thohoyandou (33%). By considering the mixing layer and meteorological conditions the factors shifted while keeping the dominant Cl-Pb and Cu-Zn tracer combinations. HIGHLIGHTS DN-PMF is a valid sensitivity test for C-PMF by reducing subjective bias during the assigning of sources to factors. | |
| dc.description.department | School of Health Systems and Public Health (SHSPH) | |
| dc.description.librarian | hj2026 | |
| dc.description.sdg | SDG-03: Good health and well-being | |
| dc.description.sdg | SDG-11: Sustainable cities and communities | |
| dc.description.uri | https://www.tandfonline.com/journals/uenf20 | |
| dc.identifier.citation | Chantelle Howlett-Downing, Johan Boman, Peter Molnár & Janine Wichmann (28 Feb 2026): DN-PMF as a Sensitivity Test for Conventional PMF (C-PMF) Source Apportionment in Three Cities in South Africa, 2017–2018, Environmental Forensics, DOI: 10.1080/15275922.2026.2628337. | |
| dc.identifier.issn | 1527-5922 (print) | |
| dc.identifier.issn | 1527-5930 (online) | |
| dc.identifier.other | 10.1080/15275922.2026.2628337 | |
| dc.identifier.uri | http://hdl.handle.net/2263/109011 | |
| dc.language.iso | en | |
| dc.publisher | Taylor and Francis | |
| dc.rights | © 2026 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/). | |
| dc.subject | Conventional positive matrix factorization (C-PMF) | |
| dc.subject | Sources | |
| dc.subject | Sensitivity study | |
| dc.subject | Fine particles (PM2.5) | |
| dc.subject | Dispersion-normalized positive matrix factorization (DN-PMF) | |
| dc.subject | Air pollution | |
| dc.subject | Particulate matter | |
| dc.title | DN-PMF as a sensitivity test for conventional PMF (C-PMF) source apportionment in three cities in South Africa, 2017–2018 | |
| dc.type | Article |
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