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On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
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On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
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On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations

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On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations
Journal Article

On the influence of vertical mixing, boundary layer schemes, and temporal emission profiles on tropospheric NO.sub.2 in WRF-Chem - comparisons to in situ, satellite, and MAX-DOAS observations

2024
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Overview
We present WRF-Chem simulations over central Europe with a spatial resolution of 3 km x 3 km and focus on nitrogen dioxide (NO.sub.2). A regional emission inventory issued by the German Environmental Agency, with a spatial resolution of 1 km x 1 km, is used as input. We demonstrate by comparison of five different model setups that significant improvements in model accuracy can be achieved by choosing the appropriate boundary layer scheme, increasing vertical mixing strength, and/or tuning the temporal modulation of the emission data (\"temporal profiles\") driving the model. The model setup with improved vertical mixing is shown to produce the best results. Simulated NO.sub.2 surface concentrations are compared to measurements from a total of 275 in situ measurement stations in Germany, where the model was able to reproduce average noontime NO.sub.2 concentrations with a bias of ca. -3 % and R=0.74. The best agreement is achieved when correcting for the presumed NO.sub.y cross sensitivity of the molybdenum-based in situ measurements by computing an NO.sub.y correction factor from modelled peroxyacetyl nitrate (PAN) and nitric acid (HNO.sub.3) mixing ratios. A comparison between modelled NO.sub.2 vertical column densities (VCDs) and satellite observations from TROPOMI (TROPOspheric Monitoring Instrument) is conducted with averaging kernels taken into account. Simulations and satellite observations are shown to agree with a bias of +5.5 % and R=0.87 for monthly means. Lastly, simulated NO.sub.2 concentration profiles are compared to noontime NO.sub.2 profiles obtained from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements at five locations in Europe. For stations within Germany, average biases of -25.3 % to +12.0 % were obtained. Outside of Germany, where lower-resolution emission data were used, biases of up to +50.7 % were observed. Overall, the study demonstrates the high sensitivity of modelled NO.sub.2 to the mixing processes in the boundary layer and the diurnal distribution of emissions.
Publisher
Copernicus GmbH