Abstract
The rapid urbanization has led to serious air pollution issues, making it crucial to effectively reduce respiratory health risks for the health of urban residents. This paper proposes an approach for adopting the PM2.5 personal intake fraction (PIF) in neighborhood street to assess respiratory health risks by considering pollutant concentrations along with the behavior patterns of three subgroups (i.e., pedestrians, cyclists, and shop vendors). PIF was indirectly predicted by combining computer vision and computational fluid dynamics simulations based on the discrete phase model. Fifty-one configurations with different building densities, porosity (dimensions of setbacks and podiums), and height variability were examined. This study found significant differences in exposure levels and behavior heterogeneity among subgroups, with risk assessment results varying under different street cross-section scenarios. From the perspective of respiratory health, the recommendations involved modify the street cross-section through setting business interface for vendors, excessive sidewalk expansion for pedestrian and cyclists, and the building configurations of the adjacent street blocks according to the street orientation to minimizing the PIF. This study provides valuable insights into the impact of street and building configurations on respiratory health risks in neighborhood street, and this assessment framework can be partially applied to other types of streets.
Published Version
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