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

**Authors:** Run Si, Jason Stafford

PMC · DOI: 10.1098/rsos.241111 · Royal Society Open Science · 2024-09-25

## TL;DR

This paper explores how immersive reality models can help people understand and reduce exposure to harmful vehicle pollutants in urban areas.

## Contribution

The novel contribution is using physics-informed immersive reality to communicate non-exhaust pollution exposure and its health risks to the public.

## Key findings

- Exposure to non-exhaust pollution peaks at the end of braking phases with deceleration rates above 3 m s−2.
- Pedestrians 1.5 m away from a car experience background pollution levels.
- Immersive reality models effectively communicate pollution data without requiring prior knowledge.

## 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.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

4 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11421894/full.md

## References

24 references — full list in the complete paper: https://tomesphere.com/paper/PMC11421894/full.md

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Source: https://tomesphere.com/paper/PMC11421894