Abstract. Urban air quality is one of the most prominent
environmental concerns for modern city residents and authorities. Accurate
monitoring of air quality is difficult due to intrinsic urban landscape
heterogeneity and superposition of multiple polluting sources. Existing
approaches often do not provide the necessary spatial details and peak
concentrations of pollutants, especially at larger distances from monitoring
stations. A more advanced integrated approach is needed. This study presents
a very high-resolution air quality assessment with the Parallelized Large-Eddy Simulation Model (PALM), capitalising on local measurements. This fully three-dimensional
primitive-equation hydrodynamical model resolves both structural details of
the complex urban surface and turbulent eddies larger than 10 m in size. We
ran a set of 27 meteorological weather scenarios in order to assess the
dispersion of pollutants in Bergen, a middle-sized Norwegian city embedded
in a coastal valley. This set of scenarios represents typically observed
weather conditions with high air pollution from nitrogen dioxide (NO2)
and particulate matter (PM2.5). The modelling methodology helped to
identify pathways and patterns of air pollution caused by the three main
local air pollution sources in the city. These are road vehicle traffic,
domestic house heating with wood-burning fireplaces and ships docked in the
harbour area next to the city centre. The study produced vulnerability maps,
highlighting the most impacted districts for each weather and emission
scenario. Overall, the largest contribution to air pollution over inhabited
areas in Bergen was caused by road traffic emissions for NO2 and
wood-burning fireplaces for PM2.5 pollution. The effect of emission
from ships in the port was mostly restricted to the areas close to the
harbour and moderate in comparison. However, the results have contributed to
implementation of measures to reduce emissions from ships in Bergen harbour,
including provision of shore power.