Micro-scale particle simulation and traffic-related particle exposure assessment in an Asian residential community

Conducting studies on sharp particulate matter (PM) gradients in Asian residential communities is difficult due to their complex building arrangements and various emission sources, particularly road traffic. In this study, a synthetic methodology, combining numerical simulations and minor field observations, was set up to investigate the dispersion of traffic-related PM in a typical Asian residential community and its contribution to PM exposure. A Lagrangian particle model (GRAL) was applied to estimate the spatiotemporal variation of the traffic-related PM increments within the community. A detailed topography dataset with 5 m horizontal resolution was used to simulate a micro-scale flow field. The model performance was comprehensively validated using both in-situ and mobile observations. The coefficient of determination (R²) of the simulated vs. observed PM_2.5 reached 0.81 by an artery road, and 0.85 in alleys without significant road traffic. The maximum increments of kerbside PM exposure concentration contributed by road traffic during rush hour were found to be 38% (PM₁₀) and 40% (PM_2.5). This synthetic method was used to assess the impact of synoptic wind and canyon orientation on residents' PM_2.5 exposure related to traffic exhaust. Perfect exponential decay curves of traffic-related PM_2.5 were found within canyons. The decrease of road-traffic PM_2.5 on five different floor levels, compared with that on kerbside levels, ranged between 42% and 100%. The results demonstrated that in complex Asian communities, Lagrangian particle models such as GRAL can simulate the spatial distribution of PM₁₀ and PM_2.5 and assess the residents' outdoor exposure.