Web application to model and visualise the spread of traffic pollution

City decision-makers have limited ability to assess the actual impact of transportation systems on air quality because available pollution detectors provide only general data and do not allow for determining the share of emissions generated by vehicle traffic. Tools that would enable analysis based on current and detailed road traffic data are lacking. Therefore, with the GRASS-NEXT project, implemented under the Polish-Norwegian Research Programme, we developed a web-based system that integrates data from portable TOPO detectors, which record detailed road traffic data for 10 vehicle categories, as well as weather and environmental data. These resources form the basis of a pollutant dispersion model, which uses the Gaussian Plume Model to calculate diffusion coefficients and total emissions of individual compounds, presenting the results on contour maps. The software was developed using multiple programming technologies, including TypeScript, Angular, Node.js, Java Spring Boot, and C + + . The solution innovatively combines data from mobile traffic detectors with a dynamic emissions model, enabling a precise presentation of the impact of real-world transportation systems. The application provides both visualisations and specific emission values in μ g / m 3 , creating a tool that addresses a gap in existing analytical systems. The system supports environmental management and transportation planning processes, enabling the assessment of the consequences of various urban logistics measures, such as vehicle access restrictions or the development of unloading infrastructure.