Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/5713
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dc.contributor.authorKneen, Melanie Aen_US
dc.contributor.authorLary, David Jen_US
dc.contributor.authorHarrison, William Aen_US
dc.contributor.authorAnnegarn, Harold Johnen_US
dc.contributor.authorBrikowski, Tom Hen_US
dc.date.accessioned2017-06-13T08:39:50Z-
dc.date.available2017-06-13T08:39:50Z-
dc.date.issued2016-
dc.identifier.urihttps://doi.org/10.1016/j.atmosenv.2015.12.016-
dc.identifier.urihttp://hdl.handle.net/11189/5713-
dc.description.abstractA case study is presented for using an unsupervised classification (Self-Organizing Map) of a global PM2.5 data product assembled from satellite retrievals (SeaWIFS, MODIS Terra and MODIS Aqua) and ground observations. The PM2.5 data products are available, on a daily basis, from August 1997 to the present, with 10 km resolutions and global coverage. In this study, a sub-set of the PM2.5 retrievals (collected over the southern African Interior) has been averaged over ten-day intervals for a period of ten years. These averaged sub-sets have been clustered using self-organizing maps to generate spatial and seasonal “PM2.5 climates” and air quality interpretations over southern Africa. Results are an indirect validation of the satellite based data product against available regional ground-based and airborne studies. The final PM2.5 aerosol climatology shows that the data product provides credible PM2.5 estimates for a region that is lacking routine aerosol monitoring data.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/za/-
dc.subjectRegional air pollutionen_US
dc.subjectPM2.5 particulate matteren_US
dc.subjectAerosol retrievalsen_US
dc.subjectAerosol climatologyen_US
dc.subjectSeaWIFSen_US
dc.subjectMODISen_US
dc.titleInterpretation of satellite retrievals of PM2.5 over the southern African Interioren_US
dc.type.patentArticleen_US
Appears in Collections:Journal Articles (DHET Subsidised)
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