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Abstract: Air pollution is the leading environmental risk to human health, with ambient air pollution causing an estimated 4.2 million deaths each year. In the GCC, the main sources of air pollution are industrial operations such as power generation and water desalination. The pollutants are dispersed in the Planetary Boundary Layer (PBL) at the bottom of the troposphere. This highly turbulent region is where the atmosphere exchanges mass, momentum, and heat with Earth's surface. The depth of the PBL is generally 1-2 km, but over deserts under intense surface heating, the PBL may exceed depths of 6 km. Regional climate models with horizontal resolutions in the range 1-100 km must rely on parametrizations to simulate the processes in the PBL; however, these parametrizations are likely not valid for the extreme depth of the desert PBL.
In this project, large-eddy simulation (LES) with an in-house developed compressible solver is used for a parametric study to assess the impact of the PBL depth on turbulence and the dispersion of pollutants. The PBL depths studied ranged from 1 km to 4 km, with an effective mesh resolution of 10 m. This highly turbulent flow is characterized by a Reynolds number of 10**8, posing a considerable computational challenge. A methodology was developed to emulate the thermal structure and turbulence of the PBL, and a passive tracer was used as stack emissions. Considerable domain dimensions were required to develop turbulence from smooth boundary inflow with implications for nesting. The results showed the height of the tracer's vertical mixing in the PBL growing nonlinearly with the depth of the PBL. This finding could pave the way to improving pollutant injection parametrization and subgrid mixing in mesoscale and global atmospheric models.
Biography: Diego Rojas Blanco is a Colombian mechanical and civil engineer with experience in diverse computational mechanics applications, including micromechanics, high-order finite element methods, and more recently, robust entropy stable numerical methods. Currently, he is a Ph.D. candidate in the Earth Science and Engineering program at KAUST, supervised by Prof. Parsani and Prof. Stenchikov. Diego is part of the Advanced Algorithm and Numerical Simulations Laboratory, of the ECRC, and the Atmospheric and Climate Modeling Research Group at KAUST. Diego is currently working on entropy stable numerical methods for LES of turbulence and pollutant dispersion in the PBL.