A thesis submitted to the Faculty of Science, University of the Witwatersrand, in fulfillment of the requirements for the degree of Master of Science. Johannesburg, 2017. / The Highveld is identified as an air pollution ‘hotspot’ area where pollutant concentrations
are elevated due to the high density of industrial and non-industrial air pollution sources. To
enhance air quality across the Highveld, it was declared a priority area to manage and
monitor pollutants to reduce their negative impact on the environment and society. Hence,
the aim of this study was to investigate ambient air pollution across the Highveld Priority
Area (HPA), using ground-level SO2, NOx and surface O3 concentrations, meteorological
parameters and Moderate resolution imaging spectroradiometer (MODIS) atmosphere
products, for January to December 2011, to develop new modelling techniques to aid in the
management of air pollution.
Results show the annual mean trace gas concentrations of SO2, NOx and surface O3 were
12.14, 14.75 and 28.77 ppb, respectively. SO2 and NOx concentrations were highest during
winter at an average of 17.56 and 20.96 ppb, where surface O3 concentrations were highest
during spring at an average of 32.82 ppb. Diurnal patterns of SO2 and surface O3 were
similar, where a midday peak occurred. NOx concentrations instead showed peaks during
traffic hours. Ambient air temperature, solar radiation, relative humidity, wind speed and
rainfall levels peaked during summer. Atmospheric pressure was relatively stable
throughout the year. Winds typically ranged from N to E up to April and from S to NW from
May. Very little variation in SO2 and NOx concentrations was explainable by meteorology, 4
to 29 % and 5 to 23 %, while the influence of meteorology on surface O3 concentrations was
more significant, 23 to 53 %. Spatial multiple regression statistical models using a cross
validation approach for model validation were made over a number of temporal scales. The
model fitting and validation processes indicated that the models were not a good fit as only
up to 69, 74 and 58 % of SO2, NOx and surface O3 concentrations with high root means
square error (RMSE) values of up to 22.10, 15.56 and 18.59 ppb, respectively, could be
explained by the models. This process revealed the potential to model pollutants across the
HPA, and as a pilot study future work can be based on this study. It is clear that spatial
modelling for pollution estimation and management is necessary as seen by the frequent
exceedances of the national and international ambient air quality standards. / XL2017
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/23542 |
| Date | January 2017 |
| Creators | Roffe, Sarah Jane |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | Online resource (204 pages), application/pdf |
Page generated in 0.0021 seconds