Abstract:
The deterioration of air quality in Lebanon is a growing environmental concern as it negatively impacts the public health, and the environment in general. According to the World Health Organization (WHO) 4.2 million premature deaths were caused by the degradation of ambient air quality worldwide in 2019. In Lebanon, the estimated average number of deaths is 4 per 10,000 people because of air pollution in 2018 and this is one of the highest rates in the MENA region alongside Egypt. Lebanon heavily depends on fossil fuels, primarily within unregulated power generation units and an unsustainable transport sector, leading to the emission of Sulfur dioxide (SO2), Particulate Matter (PM2.5 and PM10), Carbon dioxide (CO2), and Nitrogen Oxide (NOx). The energy sector in Lebanon has undergone a dramatic transformation after the economic crisis of 2019. Prior to this crisis, Beirut benefited from 22 hours of uninterrupted supply of electricity from Electricity Du Liban (EDL); however, after the crisis in 2019, these hours were cut into almost 2 hours increasing the reliance on the private diesel generators. In this work, the Gaussian model for area source was used to estimate the emissions of SO2 and PM from private diesel generators in Greater Beirut Area (GBA). The particulate matter concentration in Beirut is exceeding established international air quality standards; however, even with the increase in the sulfur dioxide concentration, it remains in the limit outlined by WHO. Moreover, the point source Gaussian model depends on logarithmic graphs to determine the dispersion coefficients. A software program was developed depending on an iterative process to determine the emission concentration in a more accurate and precise way. This tool was incorporated in a user-friendly platform to optimize stack height, find the maximum ground concentration, and the concentration from area source. It is aimed to support in air quality assessment for Lebanon and other developing countries that lacks advanced monitoring techniques.
