Influence of climate change on meteorological conditions affecting air pollution dispersion in South African air quality priority areas

Abstract

With increasing air pollution challenges, meteorological conditions regulating the concentrations of pollutants are changing due to climate change. Considering that South Africa is a climate change hotspot with three air quality priority areas that were recently expanded, it is important to investigate the influence of climate change on meteorological conditions, especially in areas plagued by air quality challenges. However, exploring such effects requires long-term historical meteorological data, which can be a challenge to obtain in South Africa. Therefore, ERA5 reanalysis datasets were compared against ground-based meteorological observations (temperature, wind speed, wind directions, rainfall, and relative humidity) using statistical measures at diurnal and annual timescales. Although there are some discrepancies, the results showed acceptable levels of agreement between simulated and observed variables across the study sites. Moreover, the model performed better in simulating annual variations than diurnal variations for all variables. After gaining a good understanding of the performance, strengths and weaknesses of the ERA5 reanalysis model, the data could be used as reference data to further explore the influence of climate change on relevant meteorological variables over a period of 40 years in South African air quality priority areas. Seasonal average temperatures increased over the study period, while for most seasons, relative humidity, wind speed, and rainfall experienced decreases. The investigation further revealed factors that may explain the variation in the atmospheric variables, and it was found that variation in time mostly played a minor role. Factors such as land use and land cover change, climate variability, anthropogenic activities and others explain approximately 85% of the variations. Each variable influences the dispersion of air pollution and interacts with pollutants differently. Therefore, the variations either enhance or reduce the pollution level across the study regions depending on their relationship