Regional modelling of air quality and aerosol-interactions over southern Africa Impact of aerosols and regional-scale meteorology

Abstract

Atmospheric trace components play a critical role in the earth-atmosphere system through their interaction and perturbation to global atmospheric chemistry. They perturb the climate through scattering and absorbing of solar radiation (direct effects), thereby impacting on the heat energy balance of the atmosphere, and alter cloud microphysical properties affecting cloud formation, cloud lifetime and precipitation formation (indirect effects). These trace components can also have adverse effects on human health, visibility and air quality (AQ) composition, including various feedback processes on the state of the atmosphere. As well as their direct and indirect effects, aerosols are important for cloud formation. They serve as cloud condensation and ice nuclei (CCN and IN) during cloud droplet and ice crystal formations. Although many connections between clouds and aerosol effects have been established in cloud physics and climate modelling, aerosol-cloud interaction (ACI) is still one of the areas of large uncertainties in modern climate and weather projections. Different models have been developed placing much emphasis on ACIs, to have robust and more consistent description processes within the meteorological and chemical variables to account for ACIs and feedback processes. Because pollutant distributions are controlled by a specific meteorology that promotes residence times and vertical mixing in the atmosphere, reliable chemical composition measurements are required to understand the changes occurring in the earth-atmosphere system. Also, because atmospheric pollution is a combination of both natural and man-made (anthropogenic) sources, to direct controlled and/or mitigation procedures efficiently, contributions of different sources need to be considered. Occasionally these are explored from a particular region or global environment, depending on a specific area of interest.A fully coupled online meteorology-chemistry model framework (WRF-Chem) is used to investigate atmospheric ACIs over southern Africa -a region characterized by a strong and intense seasonal biomass burning (BB) cycle. The large transport of aerosol plumes originating from the seasonal burning from agriculture, land-use management and various activities give rise to a unique situation warranting special scrutiny. Simulations are conducted for the 2008 dry season BB episode, implementing a chemical dataset from various emission sources (anthropogenic, BB, biogenic, dust and sea salt) with the meteorological conditions. A base line (CNTRL) simulation was conducted with all emission sources from 26 August to 10 September 2008. To probe the contribution of BB on the regional pollution and influence on ACIs, a sensitivity (TEST) simulation was conducted without BB emissions and compared to the base line. The impact of natural and anthropogenic aerosol particles is studied and quantified for the two simulations, focusing on aerosol concentration and cloud responses under different model resolutions. A statistical analysis of pollutant concentration of major regulated species and cloud variables is conducted and the percentage difference used to assess the contribution due to BB emissions. Results confirm the high variability of spatial and temporal patterns of chemical species, with the greatest discrepancies occurring in the tropical forests whereas the subtropics show more urban/industrial related emissions. Whilst CO and O3 show statistically significant increases over a number of cities/towns, the trend and spatial variability is much less uniform with NO2 and PM in most urban and populous cities. Statistical analysis of major chemical pollutants was mainly influenced by BB emissions. O3, NOx, CO and PM increase by 24%, 76%, 51%, 46% and 41% over the main source regions, whereas in the less affected regions concentrations increased by 5%, 5%, 5%, 3% and 2% when BB emissions are included. This study sheds new light on the response of cloud processes to chan

Date of Award	1 Jan 1824
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Gordon Mcfiggans (Supervisor) & David Schultz (Supervisor)