In recent years, Computational Fluid Dynamics has become a method widely used by the scientific community to study the dispersion of air pollutants in urban areas, these models allow to accurately quantify values of concentration of pollutants and how they are distributed spatially. This article seeks to analyze the effectiveness of computational fluid dynamics models and their validation methods used to estimate pedestrian exposure to Traffic Related Air Pollutants. This work proposes an exploratory methodology based on a literary review. A total of 28 articles were selected and analyzed from 455 literature published in the Scopus database between 2018-2023. The results show the effects of meteorological variables such as wind speed and wind direction on the dispersion of pollutants, especially that at higher wind speeds, they tend to disperse more quickly, which reduces the concentration of these hazards pollutants at the level of the pedestrian respiratory zone, another strategy widely used is tree planting near avenues, however, this must be done with careful analysis, since having more green infrastructure does not always translate into a reduction in pollutants near avenues. There is a tendency to use experimental data with wind tunnel, as validation of results of computer simulations, of the 28 selected articles 14 were based on this technique. Computational fluid dynamics is an advantageous tool, however, most of the estimates obtained in the literature only quantify exposure to the entry of the respiratory system, therefore, it is necessary to complement, with other models that consider the physical activity of people and thus evaluate more specifically the effect of inhaled pollutants on the entire respiratory system of pedestrians.
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Computational Fluid Dynamics models to estimate pedestrian exposure to traffic related air pollutants: A review
Published:
01 November 2023
by MDPI
in The 6th International Electronic Conference on Atmospheric Sciences
session Air Quality and Human Health
Abstract:
Keywords: Air pollution; computational fluid dynamics; pedestrian; traffic-related air pollution