%0 journal article %@ 1352-2310 %A Ramacher, M.O.P., Matthias, V., Aulinger, A., Quante, M., Bieser, J., Karl, M. %D 2020 %J Atmospheric Environment %P 117674 %R doi:10.1016/j.atmosenv.2020.117674 %T Contributions of traffic and shipping emissions to city-scale NOx and PM2.5 exposure in Hamburg %U https://doi.org/10.1016/j.atmosenv.2020.117674 %X We investigated the contribution of road traffic and shipping related emissions of NO2 and PM2.5 to total air quality and annual mean population exposure in Hamburg 2012. For this purpose, we compiled a detailed emission inventory following SNAP categories focusing on the detailed representations of road traffic and shipping emissions. The emission inventory was applied to a global-to-local Chemistry Transport Model (CTM) system to simulate hourly NO2 and PM2.5 concentrations with a horizontal grid resolution of 500 m. To simulate urban-scale pollutant concentrations we used the coupled prognostic meteorological and chemistry transport model TAPM. The comparison of modelled to measured hourly values gives high correlation and small bias at urban and background stations but large underestimations of NO2 and PM2.5 at measurements stations near roads. Simulated contributions of road traffic emissions to annual mean concentrations of NO2 and PM2.5 is highest close to highways with relative contributions of 50% for NO2 and 40% for PM2.5. Nevertheless, the urban domain is widely affected by road traffic, especially in the city centre. Shipping impact focuses on the port and nearby industrial areas with contributions of up to 60% for NO2 and 40% for PM2.5. In residential areas in the north of the port, shipping contributes with up to 20–30% for NO2 and PM2.5. Our simulation resulted in 14% of the population of Hamburg being exposed to hourly NO2 concentration above the hourly limit of 200 μg/m³, <1% to annual NO2 concentrations above the annual limit of 40 μg/m³, and 39% to PM2.5 concentrations above the annual WHO limit of 10 μg/m³. The calculation of the population-weighted mean exposure (PWE) to NO2 and PM2.5 reveals mean exposures of 20.51 μg/m³ for NO2 and 9.42 μg/m³ for PM2.5. In terms of PWE to NO2, traffic contributes 22.7% to the total and is 1.6 times higher than the contribution of shipping (13.9%). In total, traffic and shipping contribute with 36.6% to the NO2 PWE in Hamburg in 2012. When it comes to PM2.5, traffic contributes 18.1% and is 5.3 times higher than the contribution from shipping (3.4%). In total, traffic and shipping contribute 21.5% to the PM2.5 PWE in Hamburg in 2012. Two local scenarios for emissions reductions have been applied. A scenario simulating decrease in shipping emissions by instalment of on-shore electricity for ships at berth, revealed reduction potentials of up to 40% for total NO2 exposure and 35% for PM2.5 respectively. A road traffic scenario simulating a change in the fleet composition in an inner city zone, shows lower reduction potentials of up to 18% for total exposure to NO2 and 7% for PM2.5 respectively. The discussion of uncertainties revealed high potentials for improving the emission inventories, chemical transport simulation setup and exposure estimates. Due to the use of exposure calculations for policy support and in health-effect studies, it is indispensable to reduce and quantify uncertainties in future studies.