SUMO2GRAL: A tool to simplify the workflow of estimating pollutant concentrations in urban areas

Air pollution in metropolitan areas is one of their main problems, which has led to the implementation of Low Emission Zones (LEZ) in different cities worldwide. Estimating the benefits such LEZ can provide heavily depends on correctly predicting the resulting pollutant concentrations due to vehicle emissions. Yet, one of the main problems in traffic-related research is that the emission models of traffic simulators merely allow determining the mass emissions of vehicles, and not the concentrations of these pollutants as experienced by citizens. Although urban pollutant dispersion models have been developed to fill this gap, seamless integration with traffic simulators remains elusive. One of the solutions recently adopted is to create frameworks that integrate both concepts. In this work, we present a novel tool called SUMO2GRAL, that facilitates the creation of an integrated framework. In particular, it combines the SUMO traffic simulator with the GRAL pollutant dispersion model, in order to obtain reliable concentrations of urban air pollutants. Based on those results, researchers shall be able to help city administrations in their policymaking process. In addition, we demonstrate how this tool works, and compare it against a state-of-the-art solution. The validation results show that, even when an expert uses the state-of-the-art solution, our tool is still able to substantially improve the overall time spent in the process, making it about 130 times faster. This improvement helps in the process of focusing on creative tasks by offering the ability to test different scenarios in a much faster way.