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Preprints
https://doi.org/10.5194/acp-2020-166
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-166
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: measurement report 06 Apr 2020

Submitted as: measurement report | 06 Apr 2020

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This preprint is currently under review for the journal ACP.

Measurement report: Statistical modelling of long-term atmospheric inorganic gaseous species trends within proximity of the pollution hotspot in South Africa

Jan-Stefan Swartz1, Pieter G. Van Zyl1, Johan P. Beukes1, Corinne Galy-Lacaux2, Avishkar Ramandh3, and Jacobus J. Pienaar1 Jan-Stefan Swartz et al.
  • 1Unit for Environmental Sciences and Management, North-West University, Potchefstroom Campus, Potchefstroom, 2520, South Africa
  • 2Laboratoire d'Aerologie, UMR 5560, Université Paul-Sabatier (UPS) and CNRS, Toulouse, France
  • 3Sasol Technology R&D (Pty) Limited, Sasolburg, South Africa

Abstract. South Africa is considered an important source region of atmospheric pollutants, which is compounded by high population- and industrial growth. However, this region is understudied, especially with regard to evaluating long-term trends of atmospheric pollutants. The aim of this study was to perform statistical modelling of SO2, NO2 and O3 long-term trends based on 21-, 19- and 16-year passive sampling datasets available for three South African INDAAF (International network to study Atmospheric Chemistry and Deposition in Africa) sites located within proximity of the pollution hotspot in the industrialised north-eastern interior in South Africa. The interdependencies between local, regional and global parameters on variances in SO2, NO2 and O3 levels were investigated in the model. Long-term temporal trends indicated seasonal and inter-annual variability at all three sites, which could be ascribed to changes in meteorological conditions and/or variances in source contribution. Local, regional and global parameters contributed to SO2 variability, with total solar irradiation (TSI) being the most significant factor at the regional background site, Louis Trichardt (LT). Temperature (T) was the most important factor at Skukuza (SK), located in the Kruger National Park, while population growth (P) made the most substantial contribution at the industrially impacted Amersfoort (AF) site. Air masses passing over the source region also contributed to SO2 levels at SK and LT. Local and regional factors made more substantial contributions to modelled NO2 levels, with P being the most significant factor explaining NO2 variability at all three sites, while relative humidity (RH) was the most important local and regional meteorological factor. The important contribution of P on modelled SO2 and NO2 concentrations was indicative of the impact of increased anthropogenic activities and energy demand in the north-eastern interior of South Africa. Higher SO2 concentrations, associated with lower temperatures, as well as the negative correlation of NO2 levels to RH, reflected the influence of pollution build-up and increased household combustion during winter. ENSO made a significant contribution to modelled O3 levels at all three sites, while the influence of local and regional meteorological factors was also evident. Trend lines for SO2 and NO2 at AF indicated an increase in SO2 and NO2 concentrations over the 19-year sampling period, while an upward trend in NO2 levels at SK signified the influence of growing rural communities. Marginal trends were observed for SO2 at SK, as well as SO2 and NO2 at LT, while O3 remained relatively constant at all three sites. SO2 and NO2 concentrations were higher at AF, while the regional O3 problem was evident at all three sites.

Jan-Stefan Swartz et al.

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Jan-Stefan Swartz et al.

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Short summary
Statistical modelling of interdependencies between local, regional and global parameters on long-term trends of atmospheric SO2, NO2 and O3 within the proximity of the pollution hotspot in South Africa, indicated that changes in meteorological conditions and/or variances in source influences contributed to temporal variability. The impact of increased anthropogenic activities and energy demand in this region was evident, while ENSO made a significant contribution to O3 levels.
Statistical modelling of interdependencies between local, regional and global parameters on...
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