Determination Of Air Pollution From Emission Sources Using Gaussian Model Coupled With An Iterative Procedure

Abstract

The work presented in this thesis constitutes the deployment of Gaussian point-source model to calculate the maximum ground-level sulfur dioxide concentration of Zouk thermal power plant at a certain downwind distance from the stack by using different wind speed parameters for the six stability classes (A-F). Additional concentration from Standby generators was studied in comparison to the interval where only Zouk’s emissions were reaching Beirut. These standby units are randomly scattered throughout the populated areas of Beirut as well as most Lebanese cities and towns. They are operated without any control on the quality of the generators and the fuel used, and the emissions are emitted almost at ground level. The work attempts to model the accumulation of pollutants in the atmosphere, and to compare the results to the pre-crisis period, where the transport sector was almost the main source of pollutants. Accordingly, the Zouk Thermal Power plant was modeled as a point source from which the emissions reaching GBA are also modeled. Projection of emissions till 2030 has been conducted based on three scenarios: Business As Usual, Realistic, and Optimistic. The Greater Beirut Area was modeled as an area-source box model to calculate Beirut’s CenterPoint sulfur dioxide concentration. Results show the drastic impact of standby generation on the air quality in the GBA. In addition, two AI-driven prediction models were tested to predict Lebanon’s EDL grid electricity until 2030 under the same three scenarios: ARIMAX and an Elastic Net ML model.