Across the world, air quality regulations are breached due to localized high pollution episodes, or hotspots. Advances in air pollution monitoring techniques enable hotspots to be identified more effectively; however challenges remain as to how best to reduce the incidence and impact of theseepisodes. Where road traffic is the dominant source of pollutants, intelligent transportation systems (ITS) measures, including alternative trafficmanagement strategies, may be deployed to mitigate the hotspot and contribute towards regulatory compliance. However, the effective evaluation of such ITS measures requires the use of computationally expensive microscopictraffic and emissions models in order to appropriately represent changes in vehicle emission profiles. This paper demonstrates how advances in distributed computing can be combined with the latest generation of traffic and emissions models to provide robust and rapid evaluation of alternative traffic management scenarios.
Abstract