The importance of Indoor Air Quality (IAQ) has been highlighted by the COVID-19 pandemic, particularly due to the possibility of long-distance airborne transmission. Consequently, assessment of ventilation rates and estimation of infection risk has become a matter of the utmost importance. In this paper, a naturally ventilated elementary school classroom is studied, where carbon dioxide (${\mathrm{CO}}_2$) concentrations were measured during five months. Ventilation rates are calculated via a fully-mixed box model and the airborne risk of infection for SARS-CoV-2 is assessed. Risk results are found to steadily decline from winter to spring. Furthermore, analytical simulations for different scenarios are conducted. It is shown that periodic ventilation significantly reduces the transmission risk, even if it occurs only during very reduced time spans. The results show that periodic ventilation is a useful strategy for reducing the risk of any airborne transmitted disease. It is particularly well-suited for naturally ventilated environments in cold weathers, as it allows for a compromise between IAQ and thermal comfort, and does not require any modification to existing buildings.

The use of Computational Fluid Dynamics (CFD) to assist in air quality studies in urban environments can provide accurate results for the dispersion of pollutants. However, due to the computational resources needed, simulation domain sizes tend to be limited. This study aims to improve the computational efficiency of an emission and dispersion model implemented in a CPU-based solver by migrating it to a CPU–GPU-based one. The migration of the functions that handle boundary conditions and source terms for the pollutants is explained, as well as the main differences present in the solvers used. Once implemented, the model was used to run simulations with both engines on different platforms, enabling the comparison between them and reaching promising time improvements in favor of the use of GPUs.

Particle transport by fluid is probably one of the most difficult and involved subjects among fluid dynamics, with many important issues in this field still to be fully understood. The main purpose in this work was to advance the capabilities of the computational fluid dynamics (CFD) code caffa3d so to include effective numerical modeling of particle transport by turbulent fluid flow. An Eulerian mixture model was selected wherein particles are not addressed individually but rather as a whole, incorporating their effect by means of an effective local viscosity. Numerical simulation of local scour caused by a vertical impinging jet on a sand sediment bed was carried out. The nozzle velocity value were changed in order to analyze the influence of the erosion parameter in the equilibrium erosion value. The influence of internal friction angle and porosity were also analyzed. The results achieved show that the model adequately represents the different physical processes that drive the evolution of the fluid–particle mixture, reaching a good quantitative match with the results previously reported in the bibliography.

A model for representing different pollution sources in an Urban Environment is presented in this paper. An in-house incompressible flow solver called caffa3d.MBRi was used and modified in order to include the sources from chimneys, cars and houses to compute the dispersion of different pollutants simultaneously. Moreover, different urban domains with a wide variety of sources were simulated reaching promising results.