PM10 is a notorious air pollutant that often degrades the air quality in Cape Town. Previous studies have attributed high concentrations of PM10 over Cape Town to local sources, neglecting the influence of remote sources. The present study investigates the influence of remote and local pollution sources to PM10 episodes over the city. The study analysed observations from Cape Town’s air quality monitoring stations and simulations from the Weather Research and Forecasting model with Chemistry (WRFChem). The observation data were used to identify PM10 episodes over the city between 2008 and 2014 and WRF-Chem was applied to simulate the atmospheric conditions and PM10 transport over southern Africa a few days before, during, and after each episode. To examine the sensitivity of the simulations to chemistry parameterisation, two chemistry parameterisation schemes were used in the study. The two schemes are RADM2 chemistry scheme coupled with the MADE/SORGAM aerosol module (RMS) and RADM2 coupled with the GOCART aerosol module (RGC). While RMS accounts for aerosol feedbacks, RGC does not. The capability of the model (with each scheme) to reproduce the PM10 concentration and wind over Cape Town was quantified by comparing the simulations with the station observation data. To identify the paths of air parcels that arrived in Cape Town during each episode, the study employed back trajectory simulations from the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and from the WRF-Chem output. A third WRFChem simulation (KAYE) was performed in order to investigate the influence of idealized local emissions from Khayelitsha (one of the largest local sources of the pollutant in Cape Town) on the spatial distribution of PM10 concentration over the city. The results show that all the WRF-Chem simulations reproduce well the observed wind speed and direction over Cape Town during the episodes but struggle to reproduce the observed PM10. The simulations under-estimate the observed PM10 concentration over the city and, in most cases, reproduce peaks in PM10 concentration days earlier or later than the observations. However, the simulations agree with the HYSPLIT back-trajectory simulations that most of the air parcels over Cape Town during the episodes came from central southern Africa or the Namibian coast and travelled over the Kalahari, Namib, or both deserts before reaching Cape Town. The RMS simulations link the peaks in PM10 concentration over Cape Town with the transport of the pollutant from the north-west coast of southern Africa, featuring a coastal trough and a plume of PM10 along the coast. The study reveals that northwesterly flows provides a conducive condition for the long-range transport of PM10 to Cape Town, while south-easterly winds favour the transport of PM10 from Khayelitsha emissions to the city.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/30966 |
| Date | 29 January 2020 |
| Creators | Molepo, Koketso Michelle |
| Contributors | Abiodun, Babatunde J |
| Publisher | Faculty of Science, Department of Environmental and Geographical Science |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MSc |
| Format | application/pdf |
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