This is a nice piece of work, I enjoy reading it. This work provide a comprehensive evaluation of NOx high-resolution simulation over Germany. NOx is one of the most important tracer gases in the atmosphere, which largely impacts photochemistry and generate secondary pollutants, including ozone and nitrate. High resolution simulation is critical to improve the non-linear photochemical processes and heterogeneous processes, the latter of which is also important for both air quality and climate, eg. (Chen et al., 2020). The work uses a broad surface observation network and DOAS column observations of NOx to provide a valuable evaluation of the high-resolution results using different emission inventories, and help us understand the uncertainties in model and inventories. I am more familiar with modelling and possibly not the best person to comment on the observation part, while, I have collaborated with MPIC a few years ago, I trust the data is of high quality from their rigorous research style. And authors have described the observation method in details and it looks convincing for me. This manuscript is well organized and written. I am happy to recommend it for publishing.

A few minor comments may help improve the discussion.

1) line 39, “secondary chemistry”, may be better using secondary pollution?

2) A little more information on the emission inventory would be helpful. Such as, the resolution of TNO and UBA inventory, and how does seasonal variation considered? What does “fl” subtitle mean, better introduce it.

3) In conclusion, up to 50% higher human emission of NOx only have a minor effect on ambient VMRs and dSCDs, and authors think this possibly stem from the short lifetime of NOx. I feel we may want a more careful discussion here, because, no matter what time scale it is for NOx lifetime, NOx concentration is a result of the equilibrium between sources and sinks. And 50% higher of anthropogenic source has a minor impact on surface concentration, I feel it could due to two reasons: 1) anthropogenic emission is a minor source in afternoon, clearly this cannot be true over Germany, or 2) boundary layer vertical mixing is high in afternoon, this maybe more likely to be the reason. You may want to take a look of the column NOx value, VCDs. If there is a clear increase of VCDs, it could be an evidence of vertical mixing.

References:

Chen, Y., Cheng, Y., Ma, N., Wei, C., Ran, L., Wolke, R., Größ, J., Wang, Q., Pozzer, A., Denier van der Gon, H. A. C., Spindler, G., Lelieveld, J., Tegen, I., Su, H., and Wiedensohler, A.: Natural sea-salt emissions moderate the climate forcing of anthropogenic nitrate, Atmos. Chem. Phys., 20, 771-786, 10.5194/acp-20-771-2020, 2020.

Kumar et al. present a confrontation of NO₂ simulations performed with a high-resolution atmospheric chemistry model, set up over southwest Germany, with surface mixing ratio observations and ground-based MAX-DOAS observations of NO₂ vertical column densities and differential slant column densities. The simulations are performed using two emission inventories with different spatial resolutions and emission totals. An additional simulation is performed where sector-specific temporal emission profiles are applied for the high-resolution inventory. The authors report the best model performance using the high-resolution inventory with temporal variation in emissions. Next, the authors derive differential slant column densities from the model simulations and compare these to MAX-DOAS observations under different viewing angles. This allows an evaluation of the spatial and vertical distribution of NO₂ in the vicinity of the MAX-DOAS instrument.

The evaluation of the atmospheric chemistry model is comprehensive and detailed. The evaluation of dSCDs to evaluate the spatial and vertical distribution of NO₂ in the lower atmosphere seems innovative and reproducible in other model evaluation studies (from my atmospheric chemistry modelling perspective). The overall quality of the presented figures and tables, as well as their discussion in the text, is of good quality. Therefore, the manuscript is suitable for publication in AMT after addressing the following questions.

• The difference between the TNO-MACC-III and UBA anthropogenic emission inventories (70%) is remarkable and deserves further discussion.
  1. Can anything be concluded regarding the agreement per source sector?
  2. How do EDGAR emission totals compare to both inventories (as an independent estimate)?
  3. I believe TNO-MACC-III distinguishes between gridded sources (which have unit mass per grid cell per year) and point sources (which have unit mass per year). The latter should be added after interpolation to the destination model grid in order to conserve the mass balance. Not accounting for this leads to inaccurate representations of local emission peaks, and may affect domain emission totals. Please further discuss the strategy to interpolate emission data.
  4. It would be good to embed this finding in the context of the literature: e.g. Travis et al. (2016) suggest sector-specific emission reductions of 30-60% over the Southeast US, and Visser et al. (2019) report European satellite-derived emission totals of ±50% higher compared to TNO-MACC.
• Based on the model comparison with MAX-DOAS observations, can anything be concluded regarding the representativeness of surface emissions from different sources in relation to the model-observation agreement (e.g. T2 in direction of Mainz (anthropogenic footprint), vs. T4 in direction of agricultural areas).
• Appendix B: this is a highly relevant discussion, and most (if not all) models struggle to accurately capture the diurnal cycle in O₃. I believe this section can be strengthened by pointing this out, for example by referring to regional model intercomparison efforts with similar results (e.g. Solazzo et al. 2012; Im et al., 2015). Why are O₃ simulations only moderately sensitive to substantial NO_x emission differences? Can you detect an effect of model resolution on O₃ mixing ratios (e.g. by comparing domains CM07 and CM02)?

Specific comments

• Line 96: change ‘6 hourly’ to ‘6-hourly’
• Figure 1: Please increase the font size of the annotated text in the zoomed panel for increased legibility
• Line 151-154: I suggest to give some more context to the soil NO_x emission totals and how they compare to other estimates. This is especially relevant in the context of the increasing importance of soil NO_x due to decreasing anthropogenic NO_x sources (see e.g. Skiba et al. 2020)
• Line 370-371: The reference to Figure C1 now refers to the cloud classification figure, and I cannot find the figure showing Pi-MAX VCDs elsewhere in the text. Please include this figure.
• Line 589: change ‘deposited’ to ‘deposition’

References

Im, U., R. Bianconi, E. Solazzo, I. Kioutsioukis, A. Badia, A. Balzarini, R. Baró et al.: Evaluation of operational on-line-coupled regional air quality models over Europe and North America in the context of AQMEII phase 2. Part I: Ozone. Atmos. Environ., 115, 404-420, https://doi.org/10.1016/j.atmosenv.2014.09.042, 2015.

Skiba, U., Medinets, S., Cardenas, L.M., Carnell, E.J., Hutchings, N.J. Amon, B.: Assessing the contribution of soil NO_x emissions to European atmospheric pollution, Environ. Res. Lett, 16 (025009), https://doi.org/10.1088/1748-9326/abd2f2, 2020.

Solazzo, E., R. Bianconi, R. Vautard, K. Wyat Appel, M.D. Moran, C. Hogrefe, B. Bessagnet et al.: Model evaluation and ensemble modelling of surface-level ozone in Europe and North America in the context of AQMEII. Atmos. Environ., 53, 60-74, https://doi.org/10.1016/j.atmosenv.2012.01.003, 2012.

Travis, K. R., Jacob, D. J., Fisher, J. A., Kim, P. S., Marais, E. A., Zhu, L., Yu, K., Miller, C. C., Yantosca, R. M., Sulprizio, M. P., Thompson, A. M., Wennberg, P. O., Crounse, J. D., St. Clair, J. M., Cohen, R. C., Laughner, J. L., Dibb, J. E., Hall, S. R., Ullmann, K., Wolfe, G. M., Pollack, I. B., Peischl, J., Neuman, J. A., and Zhou, X.: Why do models overestimate surface ozone in the Southeast United States?, Atmos. Chem. Phys., 16, 13561–13577, https://doi.org/10.5194/acp-16-13561-2016, 2016.

Visser, A. J., Boersma, K. F., Ganzeveld, L. N., and Krol, M. C.: European NO_x emissions in WRF-Chem derived from OMI: impacts on summertime surface ozone, Atmos. Chem. Phys., 19, 11821–11841, https://doi.org/10.5194/acp-19-11821-2019, 2019.