Affiliations 

  • 1 Navigation College, Dalian Maritime University, Dalian, PR China; State Key Laboratory of Coastal and Offshore Engineering, Dalian University of Technology Dalian, PR China. Electronic address: [email protected]
  • 2 Disaster Prevention Research Institute, Kyoto University, Kyoto, Japan
  • 3 Institute of Ocean and Earth Sciences, University of Malaya, Kuala Lumpur, Malaysia
Sci Total Environ, 2023 Mar 13;877:162640.
PMID: 36921850 DOI: 10.1016/j.scitotenv.2023.162640

Abstract

Urban air quality studies have primarily focused on pollutant dispersion; however, spatial or temporal concentrations collected at discretely distributed grid points (or fixed receptors) do not reflect the actual pollutant exposure of pedestrians. Using large-eddy simulation (LES) with virtual walkers implemented, this study investigates pollutant exposure of walking agents (or moving receptors) in an urban turbulent boundary-layer flow developed over an aligned building array under the influence of different wind directions. The spatial variability of the exposure risks are found to be better captured by the moving receptors than the fixed receptors along the same agent walking tracks. We demonstrate that the actual exposure can differ significantly from results interpreted from data recorded by the fixed receptors (corresponding to Eulerian estimates) and show that large discrepancies occur in avenues near the source, wherein dispersion of the point release has not occurred on larger spatiotemporal scales. In most scenarios, optimal evacuation routes are shown to be ones that deviate as much as possible from the dominant wind direction; however, one needs to decide the priority of moving to further avenues first or immediately adjusting the walking direction. The results should serve as a useful baseline reference for environmental health impact assessment and evacuation route planning against hazardous releases of air pollutants in more complex urban environments.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.