Environment

Year of publication: 2023

In the recent years, with the growing number of vehicles on the roads in urban areas, particularly freight transport, the level of congestion and air pollution have reached a concerning level reducing the quality of life. Thus, municipalities are seeking effective solutions to address these concerns. In this regard, environmentally sensitive traffic management strategies have shown to be a promising solution to protect densely populated urban areas from high emission concentration. However, an effective strategy requires accurate estimation of spatiotemporal dispersion of emissions. This is typically achieved by employing a chain of tools contains a traffic simulator, emission model and a dispersion model. While the first two components have been frequently used to estimate traffic-related emissions, their results cannot be easily validated against empirical measurements without applying a suitable dispersion model. In this study, we propose an open-source framework for the complete toolchain to estimate emission levels in 3D urban environments taking into account terrain, buildings, and meteorological data. In order to make the framework transferable o any city around the world, we mainly rely on publicly available data and only open-source tools. More specifically, we use SUMO and its integrated emission models (HBEFA and PHEM-light) in combination with the open-source dispersion modeling tool GRAL (Graz Lagrangian Model) to achieve this goal. Subsequently, this modeling framework has been applied to a district within the city of Munich to showcase its practicality.