Discovery Early Career Researcher Award - Grant ID: DE220100552
Funder
Australian Research Council
Funding Amount
$428,025.00
Summary
Improving pollutants dispersion in street canyons for better urban living. Urban street canyons formed by tall buildings restrict dispersion of vehicle emissions. This poses severe health risks to the public by aggravating roadside air pollution, but is often overlooked in city planning. This project aims to uncover the mechanisms controlling vehicle emissions dispersion processes in urban street canyons by combining novel field experiments and numerical simulations. Expected outcomes include a ....Improving pollutants dispersion in street canyons for better urban living. Urban street canyons formed by tall buildings restrict dispersion of vehicle emissions. This poses severe health risks to the public by aggravating roadside air pollution, but is often overlooked in city planning. This project aims to uncover the mechanisms controlling vehicle emissions dispersion processes in urban street canyons by combining novel field experiments and numerical simulations. Expected outcomes include a validated tool for predicting roadside air quality, control measures for reducing air pollution and guidelines for better future urban planning. This project expects to critically assist policy makers and urban planners to effectively manage city development projects and safeguard a high air quality standard in our cities.Read moreRead less
Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice mode ....Rethinking walking infrastructure: AI-assisted footpath network modelling. The project aims to develop new macroscopic and network wide transport modelling and optimisation methodologies specific to walking suitable for large scale footpath network planning applications. The expected outcomes of this project are a novel Artificial Intelligence (AI) assisted tool for automated generation of footpath network attributes, and a set of equilibrium and non-equilibrium seeking walking route choice models driven by real-world individual walking trajectory data. This project will deliver a step-change in transport planning for walking infrastructure that will lead to increased active transport and improved urban infrastructure planning, thereby resulting in significant gains in population and environmental health.Read moreRead less