ESROP Global — Imperial College London — Development of Road Surface Sampling and Imaging Robot

Fine particulate matter such as PM10 and PM2.5 can contribute to negative health impacts, poor air quality, and climate change. A major source of these particles in urban environments is dust generated by vehicle traffic and wind-driven resuspension, a source not well understood despite its importance. Specifically, key factors such as dust surface loading and surface conditions of roads cannot be reliably assessed due to the lack of practical, repeatable methods for measurement and assessment under real-world conditions.

This project aims to address this by expanding on a prototype sampling system based on a small remote controlled robotic platform. The system will be equipped with additional modules to enable higher time resolution particulate matter measurements using a small optical particle counter, as well as a camera to record road surface texture. By combining particulate measurements with surface condition data, the project will improve understanding of how road dust is generated and resuspended. Participating institutions will benefit from improved measurement capabilities, higher-quality data, new research opportunities, and enhanced capacity to address urban air quality challenges.

Faculty Supervisor:

Arthur Chan

Student:

Partner:

Imperial College London

Discipline:

Engineering

Sector:

Education

University:

University of Toronto

Program: