A Numerical Modeling Study of the Impact of Air Quality in the Arabian Peninsula

Abstract

Summertime in the Arabian Peninsula is characterised by frequent dust storms, anthropogenic emissions from local fossil fuels combustion, long-range transport, and favourable conditions for the photochemistry reactions that are more likely to degrade the air quality in the region. This research aims to investigate the air quality over the Arabian Peninsula using a locally modified version of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem), version 3.8.1. The model simulations are performed over tripletnested domains at grid resolutions of 36 km, 12 km, and 4 km, each over the Middle East, Arabian Peninsula, and the Northern part of Oman, respectively. The first study investigates the impact of uncertainty of boundary conditions, emission sources and model spatial resolution on predicting atmospheric dust loading. Modelled Aerosol Optical Depth (AOD) was evaluated against ground measurements AERONET (AErosol RObotic NETwork) and satellite data in addition, simulated particulate matter with an aerodynamic diameter smaller than 10 and 2.5 micrometres (PM10 and PM2.5, respectively) were evaluated against measurements from the AQABA (Air Quality and Climate Change in the Arabian Basin) campaign, and ambient air quality monitoring stations. The WRF-Chem simulations were significantly influenced by the global model data used as boundary conditions; data taken from The Community Atmosphere Model with Chemistry (CAM-chem) simulations was the best that was tested here. The second paper investigates the formation of the secondary gas pollutants, PM1 components and OH reactivity over the Arabian Peninsula using in-situ data from the AQABA-ship campaign, as well as remotely sensed data from satellites. We conclude that the discrepancies in the results between WRF-Chem and the AQABA-ship campaign data are likely most strongly influenced by biases in the anthropogenic emission inventory. The third paper studies the disease burden due to ambient PM2.5, O3 and NO2 exposures in the study region. Using a logarithmic concentration-response function, we estimate the short-term health impacts of different air pollutants exposure for the Gulf Cooperation Council (GCC) countries. The model-measurement uncertainty (likely to be influenced by boundary and initial condition and emission uncertainties presented in the first two papers) leads to uncertainties in health impacts, which will also be affected to some degree by model resolution.

Date of Award	31 Dec 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Gordon Mcfiggans (Supervisor) & David Topping (Supervisor)