Exposure risk to carbon monoxide concentrations inside a diesel-based bus rapid transport system: a CFD-Monte Carlo modeling approach

Abstract Bus rapid transit (BRT) vehicles are common microenvironments in urban areas. In some cities, these BRT diesel-powered, which makes them highly pollutant. Recent studies report high levels and exposure risk to particulate matter vehicles. Nevertheless, extensive research has yet be published, including gaseous pollutants (e.g., CO). CO) not been published. This aims evaluate the self-pollution of buses terms exhaust gasses. For this, measurements computational fluid dynamics (CFD) were used. Results suggest that pollutant concentrations stay low during most trips. However, areas have significant swings peaks due cycle. Here, we used CFD modeling dispersion CO inside outside bus. results show bus rear highest concentrations, with a mean ratio 12%. Additionally, developed method based on source-receptor relationship quantify impact emissions reduction self-pollution, showing technological replacement current diesel would reduce and, therefore, passenger exposure. Finally, since may inaccurate, an uncertainty analysis was using Monte Carlo obtain confidence interval 90% for variables linked self-pollution.