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Clean Air Journal

On-line version ISSN 2410-972X
Print version ISSN 1017-1703

Abstract

MUYEMEKI, Luckson; BURGER, Roelof  and  PIKETH, Stuart J.. Evaluating the potential of remote sensing imagery in mapping ground-level fine particulate matter (PM25) for the Vaal Triangle Priority Area. Clean Air J. [online]. 2020, vol.30, n.1, pp.1-7. ISSN 2410-972X.  http://dx.doi.org/10.17159/caj/2020/30/1.8066.

The quality of air breathed in South Africa is of great concern, especially in industrialised regions where PM25 concentrations are high. Long term exposure to PM25 is associated with serious adverse health impacts. Traditionally, PM25 is monitored by a network of ground-based instruments. However, the coverage of monitoring networks in South Africa is not dense enough to fully capture the spatial variability of PM25 concentrations. This study explored whether satellite remote sensing could offer a viable alternative to ground-based monitoring. Using an eight-year record (2009 to 2016) of satellite retrievals (MODIS, MISR and SeaWIFS) for PM25 concentrations, spatial variations and temporal trends for PM2.5 were evaluated for the Vaal Triangle Airshed Priority Area (VTAPA). Results were compared to corresponding measurements from the VTAPA surface monitoring stations. High PM25 concentrations were clustered around the centre and towards the south-west of the VTAPA over the highly industrialised cities of Vanderbijlpark and Sasol-burg. Satellite retrievals tended to overestimate PM25 concentrations. Overall, there was a poor agreement between satellite-retrieved PM25 estimates and ground-level PM25 measurements. Root mean square error values ranged from 6 to 11 μg/m3 and from -0.89 to 0.32 for the correlation coefficient. For satellite remote sensing to be effectively exploited for air quality assessments in the VTAPA and elsewhere, further research to improve the precision and accuracy of satellite-retrieved PM25 is required.

Keywords : Satellite retrievals; ground-based data; PM25 concentration; spatial variations.

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