Evaluating exposure to vehicle pollutants using physics-informed immersive reality models

Run Si, Jason Stafford*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Major health risks and chronic diseases are caused by exposure to unregulated particle pollutants from road, tyre and brake sources. Here, we use large-eddy simulations to identify local exposure to these harmful pollutants and build a physics-informed immersive reality experience to communicate outcomes with the general public for health guidance. Our analysis reveals that exposure to non-exhaust pollution is greatest at the end of braking phases, when deceleration rates are above 3 m s−2, diminishes to background levels for pedestrians located 1.5 m away from a car, and is reasonably insensitive to the car type. We show that by using immersive reality models to visualize pollution data in a human-centric format, people could identify pollutant sources and health risks, and understand how to navigate urban spaces for reduced exposure. This was achieved without any prerequisite knowledge and with minimal dependency on educational background, suggesting the approach can support public health guidance, policymakers and urban planners towards improving air quality in urban environments.
Original languageEnglish
Article number241111
Number of pages9
JournalRoyal Society Open Science
Volume11
Issue number9
DOIs
Publication statusPublished - 25 Sept 2024

Keywords

  • air quality
  • human-centric
  • non-exhaustemissions
  • pollution modelling

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