In "Interpreting GEMS geostationary satellite observations of the diurnal variation of nitrogen dioxide (NO2) over East Asia", the authors compare NO2 column amounts retrieved from the GEMS satellite and surface Pandora measurements with column amounts simulated by GEOS-Chem. They find that the three datasets broadly agree, although better in winter months than summer. They then use tendency diagnostics output by GEOS-Chem to attribute diurnal variations of the NO2 column to emissions, chemistry, and transport. From this, they conclude that diurnal variation of NO2, as observed by GEMS, can be used to estimate NOx emissions in winter months and chemical loss in the summer months, at the scale of an urban area, if the contribution of transport is accounted for using either a mass balance approach or a chemical transport model.

To me, this paper has the sense of one setting the foundation for future studies. That is fine, and even good to have a relatively short paper focused on demonstrating the necessary foundational concepts, which future papers can point directly to, rather than citing a subsection of larger paper using diurnal information to probe chemical loss or emissions. However, I have one primary concern: it is not clear to me how general these results are. If that concern is addressed, I recommend publication in ACP.

The crux of my concern is that, as I understood the methodology, this conclusion rests on the chemical loss of NO2 being minimized in winter months, such that the diurnal variation is driven almost entirely by transport and emissions. This does seem likely, at least in mid-latitude cities. However, this may not be true in tropical or sub-tropical areas where winter photochemistry does not decrease as significantly relative to summer. Likewise, this seems to rely on emissions being similar in the winter and summer, such that the diurnal variation in the summer can be decomposed into contributions from the unknown chemical loss rate and the emissions rate inferred from winter data. Figure 7 shows that the changes due to chemical loss and emissions are similar magnitudes, therefore if the emissions were not the same as in the winter, that would introduce considerable uncertainty to chemical lifetimes derived from the diurnal variation in NO2 columns.

I see two routes towards addressing this:

1. The simplest approach would be to explicitly limit the conclusions to Seoul and Beijing. This would still allow this paper to serve as the foundation for future studies of NOx lifetime and emissions for most cities in the GEMS and TEMPO fields of regard, provided the similarity of their winter and summer emissions can be shown.

2. The other route I see would be to expand this manuscript to establish a framework for how to evaluate whether a city would be suitable for this kind of analysis. This would mostly consist of being more explicit about the criteria used to determine whether the necessary conditions are met, e.g.:

• How do you tell that the CTM used in the study is adequately representing transport - is there a confidence level within some observations it must meet?
• How small must the chemical lifetime term in winter be (absolutely or relative to the other terms) such that the winter analysis will produce a good estimate of NOx emissions?
• How similar must winter and summer emissions be to not result in a large uncertainty on the summer chemical lifetimes? How do you test that the emissions are actually this similar, without relying on an emission inventory that may not correctly represent the seasonal variation in NOx emissions?

For this route, it would probably be necessary to find examples of cities that violate these conditions and show that the emissions and lifetimes that would be derived from the diurnal information are incorrect. If this is outside the desired scope, the the first route might make more sense.

Specific comments

l. 123: What about the accuracy of the free troposphere NO:NO2 ratio? The Yang et al. (2023) citation given does seems to examine that and conclude that the model performs reasonably well compared to KORUS-AQ aircraft data. Given that models in the past have exhibited a pernicious bias in the free tropospheric NO:NO2 ratio (e.g. Travis et al., 2016), it would be good to state that explicitly here, if that was indeed the conclusion of Yang et al. (2023).

l. 138: Why did you specifically remove data with quality flag = 12? Is that the standard recommendation in the Pandonia documentation, or did you have a specific reason to do so?

l. 141: Is there a specific reason to use GEOS FP over a retrospective product like MERRA-2? It seems like a retrospective met product would remove some uncertainty in met variables for a study using past data.

l. 195 and Fig. 4: it might be nice to include a scatter of the GEOS-Chem minus Pandora and GEMS minus Pandoa NO2 columns versus hour of day in order to show that GEMS and GEOS-Chem are getting more than just the average diurnal pattern (i.e. is there more scatter in the early morning and late afternoon than near noon, or is the uncertainty pretty consistent). From Fig. 3, it's hard to know what hours of the day the scatter is.

l. 221: I was surprised to see the NO + HO2 pathway but not the NO + RO2 pathway; my initial assumption is that if there is enough HO2 to react with NO, then there would also be RO2 as part of the process of producing HO2. Is it just that, in this environment, most of the RO2 either self-terminates or forms alkyl nitrates instead of generating NO2?

l. 250: I'm a little confused by the statement "Without the transport loss term, the NO2 column in summer would still increase over the course of the day." If all you're trying to say is that the net change in NO2 would be positive for all hours of the day without the transport term, I see that. But the net tendency is closer to 0 at the afternoon peak than the morning peak, and the trend into the night looks like it would go up with or without transport. I'd like if this statement could account for those nuances better, or perhaps it would make more sense if it was clearer what conclusion this statement is aimed at supporting.

l. 277: How did you choose 6 m/s as the dividing wind speed?

Fig. 4: Why do panels c and e have one fewer circle than panel a, and likewise for d and f versus b?

References

Travis et al. "Why do models overestimate surface ozone in the Southeast United States?" 2016, https://doi.org/10.5194/acp-16-13561-2016%

Review of "Interpreting GEMS geostationary satellite observations of the diurnal variation of nitrogen dioxide (NO2) over East Asia" submitted to ACP by Laura Hyesung Yang and colleagues in December 2023.

This paper reports on a detailed analysis of the diurnal cycle in NO2 as observed with the geostationary sounder GEMS over Seoul and Beijing by  comparing the satellite-observed winter and summer diurnal variations with those from both a GEOS-CHEM simulation and Pandora ground-based  column measurements. From this analysis, the relative importance of emissions, chemical loss, and transport is derived (qualitatively). 

In my opinion, the paper is clearly written and based on sound methodology. As one of the first analyses of the diurnal variations in GEMS observations, it definitely deserves publication.  Besides the comments and questions already raised in CC1 (by Fei Yao) and RC1 (by Josh Laughner), I have a few additional (minor) questions/comments: 

Sect. 2.1: GEMS data: Any quality assessment for the official SCDs you can refer to? Some teams decide to not only use their own AMFs, but also redo the DOAS fit (e.g., Lange, K. et al.: Validation of GEMS tropospheric NO2 columns and their diurnal variation with ground-based DOAS measurements, EGUsphere, https://doi.org/10.5194/egusphere-2024-617, 2024.) 

Sect. 2.3: You did not consider running the model at a higher spatial resolution, or is that not trivial? I assume you have the emission and meteo data at higher resolution? 

Sect. 2.3: The need to scale the emission inventory data to better reflect the current situation is clear, but is a country-averaged scaling factor detailed enough? There are probably strong differences between rural and urban NO2 reductions over the past 5-10 years.

Sect. 2.3: It would have been nice to have/repeat here a figure with the diurnal variation in the AMF. How does its amplitude compare to that in the final VCDs? 

Conclusions: 

-line 310, "We updated NOx emissions...". In fact, besides the country-wide scaling factor applied to the emission inventory data, you don't write much about the feedback your analysis gives on these inventories. Was the country-wide scaling sufficient? 

-line 314, "Diurnal variation of ..." This only holds for urban, polluted environments. In background conditions, the diurnal cycle of the total column is determined by the stratosphere.