Spatial distribution of ambient air quality in the Cape Town central business district

Abstract

The scourge of ambient air pollution exposure has been described as a public health threat facing the 21st century generation. Majority of countries worldwide are exposed to high levels of air pollution exceeding the prescribed exposure limits. In developing countries, exposure assessment of air pollution is a constant challenge even though air pollution is a public health risk. Literature indicates that in developing countries ambient air pollution is generally monitored using fixed air quality monitoring stations. This practice is associated with the limitations to capture the spatial variability of air pollutants. The aim of this study was to map the spatial distribution of ambient air quality in Cape Town CBD using Geographic Information System (GIS). The study used ambient air quality secondary data (raw data) retrieved from City of Cape Town (CoCT) Air Quality Monitoring (AQM) stations for particulate matter and nitrogen dioxide. There are two monitoring stations located at Cape Town CBD which are Foreshore AQM and City Hall AQM. Each station is designed to collect data on a particular pollutant. For instance, the Foreshore AQM station is designated to measure PM pollutants whilst the City Hall AQM station measures the NO2 pollutants. Moreover, these stations collected data intermittently, as a result, the current data obtained from the CoCT municipality mostly covered the years of 2017 to 2018. The results of this research were presented and analysed using ArcGIS 10.8 pro a product of ESRI. Heat maps were produced using the mean concentration of geostatistical analysis called the Inverse Distance Weighted (IDW) interpolation method. The graphs and tables were produced using a Microsoft Excel spreadsheet. The findings of the study show a distinct spatial variation that PM10 was the main pollutant in the CBD with a high concentration between summer and winter within the years of 2017 and 2018 while NO2 pollutant was lighter. The study further indicated that meteorological conditions such as wind speed and temperature could have a correlation close with the ambient air pollutants and play an important role in the spatial distribution of PM10 and NO2. Although the meteorological factors are not studied in this study, the findings were comparable with others studies conducted globally. Moreover, the national traffic roads entering the CBD, industrial harbour and dense residential areas with high buildings were considered in ascertaining as the pollution hotspot in the CBD. The study recommends the use of meteorological data to study the spatial distribution variability in a region as it has an important role in the distribution of ambient air pollutants. It was also noted that the fieldwork should be carried out because it would provide primary data and a lot of details compared to relying on secondary data.