Satellite retrievals of NO2 columns are used to determine NOx emissions from power plants and cities. They are increasingly used alongside CO2 retrievals to calculate emissions from these sources. However, the effect of NOx chemistry and transport on NO2 columns is often overlooked. To address this issue, Wu et al. have developed a model that incorporates a simplified representation of NOx chemical loss within the STILT Lagrangian particle dispersion model. It includes additional features such as a column weighting module to account for retrieval averaging kernel profiles and an error analysis module. The model is evaluated against TROPOMI NO2 observations from three power plants and two cities. The manuscript covers the model's advantages, limitations, and applications such as using NO2-to-CO2 enhancement ratios to estimate CO2 emissions and identifying wind biases in meteorological data.

While this work is generally sound and well-presented, there are areas that I think need attention.

1. NOx chemical tendency (Sect. 2.1):
   1. It appears that the model excludes heterogeneous NOx chemistry in aerosols. If this is indeed the case, it is important to discuss the resulting errors arising from this omission. Alternatively, if heterogeneous NOx chemistry is included, please clarify, and modify Fig. 1 accordingly to reflect this information.
   2. The NOx chemical tendency is parameterized as a function of NOx concentration and the solar zenith angle. It is unclear why these were the only two variables chosen and whether they account for most of the variation in the NOx chemical tendency. Knowing the fraction of variation explained by these variables would be useful. I expected temperature (as a proxy for seasons) and the NO2/NO ratio to be potentially important variables.
   3. The calculation of the NOx chemical tendency was based on WRF-Chem simulations for three cities: Los Angeles, Shanghai, and Madrid. The rationale behind selecting these specific cities seems arbitrary. They are unrelated to the power plants and cities that were chosen for model evaluation. It would be helpful to have an explanation for this choice.
   4. The assumption of the NOx chemical tendency being independent of height (Eq. 2) is not accurate considering the vertical gradients of NOx near the surface during nighttime and early mornings. It seems important to discuss any limitations arising from this.
   5. It would be useful to assess the consistency of the NOx chemical lifetime from WRF-Chem to the available observations, although limited.

1. NO2-to-NOx ratio (Sect. 2.2):
   1. The reactions of NO + HO2 and NO + RO2 to form NO2 are excluded, but they are important in the boundary layer.
   2. Line 242: Please clarify how the NOx chemical tendency in the model change when ozone is titrated near high emitters.

1. Eq 1: The processes of NO2 dry deposition and mixing between the mixed layer and the free troposphere seem to be neglected.
2. Eq. 5 assumes that the model transport and chemistry errors are independent, when in fact these errors are related.
3. Fig. 5 and elsewhere: Please clarify how tNO2, the tropospheric NO2 column, is converted to a volume mixing ratio.
4. Line 382: Considering the model’s sensitivity to errors in the wind direction and speed, it may be better to use winds from reanalyses datasets or to bias correct the model using nearby observations. This seems important for the inversion work planned in the future. Are there other ways to reduce this error?
5. Lines 564-570: These lines are unclear.

This paper introduces STILT-NOx, a Lagrangian chemical transport model, evaluates it against satellite based column observations of NOx, and presents various sensitivity studies. The paper is well written, and I recommend publishing after the following minor comments are addressed.

General comments:

Interparcel-mixing: I was a bit surprized to see the 3-hour timescale for mixing within a volume with a horizontal of 1km x 1km and a vertical extend from surface to PBL top described as “relatively fast mixing”. Given the fact that the plume emitted from a power plant, when transported over 3 hours (or 30 km for typical winds speeds of 10 m/s within a well-developed PBL), and given the shape of typical plumes seen from satellite imagery, can the mixing time scale not be estimated from that? Based on that I would expect that within three hours mixing likely occurs over much larger “boxes”. This is along the thought that dispersion/mixing is similar when running LPDMs backward and forward as shown in the Lin et al. 2003 paper, so forward mixing as needed for chemistry should be similar to backward mixing (or spreading of particles emitted at the same time). Would a smaller mixing timescale increase the impact of mixing, as with a 3-hour time the impact was found to be less than 5% (line 356)? Was that assessed when comparing no-mixing (i.e. infinite timescale) with mixing turned on? I think this deserves a bit of attention, as it keeps puzzling me that given the quite nonlinear property of NOx chemistry mixing at those scales does not seem to matter in chemistry-transport simulations.

Rotation of wind: As the wind changes significantly within the atmospheric boundary layer with height (the Ekman spiral), differences between modelled wind direction and the direction apparent from the observed plume can also be related to inaccuracies in the plume release height distribution, potentially associated with plume rise of the buoyant exhaust. I would recommend this to be discussed.

Specific comments:

Fig. 3: which WRF-Chem runs were used? Before three different cities were mentioned, are all those simulations included in Fig. 3?

L200: Were the WRF-Chem simulations also selected for cloud-free conditions?

Fig. 5 b and d: the color code is missing, or am I overlooking something?

L394: in table S1 the RMSE values range from 0.11 to 0.25 ppb

L 412: “fast-growing” is relative, Baotou certainly has a faster growth in population than Phoenix

Fig. 8 a: What does RMSP stand for?

Table 1 in the supplement should be named “Table S1”

Fig. S6: please use axis titles that clearly indicate v1 and v2 in all figures

Fig. S7: the symbols in the legend don’t quite fit with those in the figure. Triangles should be should only for EDGAR estimates, not for EPA.

Fig. S10 a and b: please use fewer x-axis labels