%0 journal article
%@ 0941-2948
%A Bewersdorff, I., Aulinger, A., Matthias, V., Quante, M.

%D 2009
%J Meteorologische Zeitschrift
%N 1
%P 41-53 
%R doi:10.1127/0941-2948/2009/351
%T The effect of temporal resolution of PAH emission data on transport and deposition patterns simulated with the Community Multiscale Air Quality modelling system (CMAQ)
%U https://doi.org/10.1127/0941-2948/2009/351
1 
%X The effect of different temporal resolutions of polycyclic aromatic hydrocarbon (PAH) emission data on transport and deposition patterns was analysed in a sensitivity study. Simulations were performed with the Community Multiscale Air Quality modelling system (CMAQ) for Europe for the year 2000 on a 54 × 54 km2 grid. The carcinogenic benzo(a)pyrene (B(a)P) was used as a representative for the group of PAHs. The official emission data are only available as one-year bulk emissions. The major emission sources of B(a)P vary in fact within seasonal, weekly and diurnal cycles. Therefore different approaches for the temporal disaggregation of the bulk emissions were developed and their effects were tested. The inclusion of a seasonal variability leads to an increase in the modelled annually averaged near-ground concentrations and annually accumulated depositions. Additional effects of the emissions with the most detailed time-resolution, i.e. considering weekly and diurnal cycles, are only visible on a regional scale and particularly in summer. A non-linear relation between the emissions and the concentrations is most evident in connection with the seasonal cycle in January and with the weekly and diurnal cycle in July. The effects of the diurnal variation of the emissions comply with a more efficient vertical transport during daytime. A comparison of the modelled concentrations obtained with seasonally resolved emissions with measurements at two different sites in Germany shows correlation coefficients of 0.62 and 0.74 for the four selected months. The magnitude of the summer-winter differences in the observed concentrations can be best reproduced by the model with the seasonal variations in the emission data.