The impact of traffic emissions on air quality in the Berlin-Brandenburg region – a case study on cycling scenarios

Kurzfassung

Many European cities continue to struggle with exceedances of NO2 limit values at measurement sites near roads, of which a large contribution is attributed to emissions from traffic. In this study, we explore how urban air quality can be improved with different traffic measures using the example of the Berlin-Brandenburg region. In order to simulate urban background air quality we use the Weather Research and Forecasting model with chemistry (WRF-Chem) at a horizontal resolution of 1km. We use emission input data at a horizontal resolution of 1km obtained by downscaling TNO-MACC III emissions based on local proxy data including population and traffic densities. In addition we use a statistical approach combining the simulated urban background concentrations with information on traffic densities to estimate NO2 at street level. This helps assessing whether the emission scenarios studied here can lead to significant reductions in NO2 concentrations at street level. The emission scenarios in this study represent a range of scenarios in which car traffic is replaced with bicycle traffic. Part of this study was an initial discussion phase with stakeholders, including policy makers and NGOs. The discussions have shown that the different stakeholders are interested in a scientific assessment of the impact of replacing car traffic with bicycle traffic in the Berlin-Brandenburg urban area. Local policy makers responsible for city planning and implementing traffic measures can make best use of scientific modeling results if input data and scenarios are as realistic as possible. For these reasons, the scenarios cover very idealized optimistic (“all passenger cars are replaced by bicycles”) and pessimistic (“all cyclists are replaced by cars”) scenarios to explore the sensitivity of simulated urban background air quality to these changes, as well as additional scenarios based on city-specific data to analyze more realistic situations. Of particular interest is how these impact street level NO2 concentrations.