The manuscript “Tropospheric and stratospheric NO retrieved from ground-based FTIR measurements” by Zhou et al presents findings in the retrieval of NO using ground-based solar absorption FTIR at two sites, Xianghe (polluted) and Maido (background/pristine), contrasting the retrieval sensitivity. The work presented fits well within the scope of this journal. Below I have a short list of comments/suggestions that the authors may want to consider for the final version.

Major comments

1. I find that the manuscript lacks sufficiently novel findings in the retrieval strategy. As authors mentioned in the introduction, until now, there are few studies focusing on FTIR NO retrieval and past studies have shown little sensitivity in the troposphere. However, in this work authors show results of a single retrieval strategy, i.e, a single micro-window of NO2 has been adapted from past studies, e.g., Notholt et al. (1995). Since the manuscript tries to show the retrieval of NO in the troposphere I was expecting to see a thorough description of optimized windows and retrieval parameters, instead authors only mentioned what was included but do not show an optimization. Are there more micro-windows appropriate for NO?. If there are no other suitable windows for NO I highly suggest mentioning it. In general, a description of the optimization is missing. 
2. It is concluded that tropospheric NO is not well retrieved during the summer because of high water vapor abundance. My understanding from the manuscript is that high water vapor reduces the signal to noise ratio. From my previous comment, is there a region where water vapor has less influence?. Also, I highly recommend checking the zenith angle dependency in the summer vs winter. In my opinion, it may have an effect, for example when the zenith angle is high the optical path may be more sensitive to lower tropospheric air mass, hence NO may be retrievable during high zenith angles. Do measurements in winter vs summer cover the same zenith angle ranges?
3. There is a contrast between Xianghe (polluted) and Maido (background), however it is not mentioned what would be the detection limit of the NO using these observations. Please include an assessment in the detection limit. 
4. Authors show correlation between NO and CO measured by the same instruments. While NO and CO may have the same common emission sources ther are very different species, e.g., CO lifetime is significantly larger and can be transported from other regions, etc. Are there any co-located or close-by in-situ measurements of NOx that can be used to see tropospheric columns and enhancements?. I would expect some correlation between in-situ and retrieved lower tropospheric NO since the averaging kernels show high sensitivity in the boundary layer. 

Specific comments

In the abstract: Nitric oxide (NO) is a key active trace gas in the atmosphere, which contributes to form “bad” ozone (O3) in the troposphere and to the destruction of “good” O3 in the stratosphere. I highly recommend avoiding good/bad ozone. Instead, something like this: 

“Nitric oxide (NO) is a key active trace gas in the atmosphere, which contributes to form harmful ozone (O3) in the troposphere and to the destruction of O3 in the stratosphere”

Sometimes ozone is spelled other times O3 is used, be consistent in the manuscript and I highly recommend using “ozone”. 

P2,l26. It is mentioned that at Xianghe the NO is high, please include values.

P2, l31. Is there a reason for only using MIPAS? Why not compare it to ACE-FTS?

P3. In the description of FTIR sites, please add additional information such as resolution of FTIR measurements, time resolution, i.e., how often do you measure in the region of interest?. Are there additional in-situ measurements of NO around Xianghe & Maido?. It is mentioned that NOx annual emission at Xianghe is one of the largest around the world, could you include typical concentrations comparing Xianghe and Maido?

P4, Figure 1. The obs-cal is shown in the upper plot but in the bottom plot they are not shown, maybe adding the obs and calc in the bottom plot would be more clear.

P4. I have several comments/suggestions regarding the NO a priori profile:

• CAM-Chem is used at Xianghe because WACCM underestimates surface NO concentration. However, CAM-Chem is used up to 50 km, which potentially makes the stratospheric a priori different from WACCM. I wonder why CAMChem was not used only in the lower troposphere then WACCM to use similar a priori for Maido and Xainghe?. Did you assess the impact of different a priori profiles in the stratosphere?
• Likely NO shows a strong seasonal cycle, did you assess monthly prior profiles?

P5, L2-L8. How is the SNR defined?. Are the spectra compared in the summer/winter taken at a similar zenith angle?, maybe I miss it but how does the SNR affect the DOFs?

P6, l10. It is mentioned that summer retrievals are limited. It is concluded that the decrease of DOFs in the summer is due to low SNR because of greater water vapor columns. One more thing to assess, in my opinion, is the dependency in the sza, could you please indicate if measurements over summer & winter cover similar zenith angles?. Maybe the optical path using high zenith angles has more sensitivity over the lower troposphere, hence greater DOFs?. In general, the sza dependency is missing and may also contribute to low DOFs in the summer. 

P9, l12-15. First it is described that NO decreases after 14:00 for some months, e.g. January but different for other months, e.g., February. Please add a reason for this. Furthermore, if the fittings are not robust I suggest removing them. 

P13, l4. I suggest adding, maybe next to Figure 9, the monthly mean seasonal variation of MIPAS and FTIR (since there are no coincident dates). This would allow the reader to see the difference in amplitudes mentioned in the text. 

P15. L2-9. In the context of Figure 10, the manuscript indicates that when the DOF is larger than 0.5 in the troposphere there is no linear relationship between the retrieved tropospheric and stratospheric partial column. However, I do see it as enhancements of NO2 in the troposphere are not correlated with stratospheric NO2, how do you  disentangle the atmospheric chemistry and the retrieval DOFs?

Have you explored Figure 10 but color coded by SZA?

General Comment:

The paper by Zhou et al is a report of column measurements of NO from two sites, one in a polluted area of the Northern Hemisphere  (Xianghe, China), and the other in a remote part of the Southern Hemisphere (Maido, ReUnion Island). These data also represent a polluted urban area (in the troposphere) and non-polluted site. This would appear to be the first report of a successful analysis of NO in the troposphere from a ground based FTIR, a nuiance that the authors do not explicitly state. Ground-based NO columns has been reported before in the literature, and invariably from NDACC sites that do not in general, see the sort of heightened levels of NO that is reported at Xianghe. So while the stratospheric columns and comparison with satellite data is not new, the tropospheric partial columns of NO are unique, at least as a first report in the literature. Similar data at other Chinese sites may exist and indeed, other potential NDACC sites near large cities that may or may not have enhanced levels of NO near the ground, but the potential is there to explore.

The methods used follow reasonably standard software procedures that have been developed over many years within the NDACC, but NO is not one of the normal target molecules reported by this network. The authors here represent an experienced team who have a very good track record in this area of atmospheric spectroscopy. The paper is not claiming to provide an extensive description of their method, but refer to a few papers in the literature where this is done. A few more details on how they derived some of the parameters used in the analysis, should be fleshed out a bit, as is mentioned below in the comments sections.

Given that NO2 is an integral part of the NOx family along with NO, it would have been an obvious addition to add NO2 to this analysis. This added molecule is readily available in the FTIR spectra, as the authors know, so this would have been an obvious choice to make alongside CO. Or alternatively, in a city like Xianghe, are there air quality monitors like a NOx box that measures NO/NO2?

There is also the question of why there is not a modelling component to this paper?

So really the question is: is this paper about a new measurement capability (tropospheric NO), or a comparison between a polluted and non-polluted site, or a satellite comparison, or what?

So before this paper is published, the purpose of this paper and the new novel aspects need to be clearly pointed out.  

The level of written English in general ok, but there are a few grammatical issues which are listed in the comments.

Specific comments:

1. P1, L7: “ …almost not able to be retrieved …” => “…is very difficult to retrieve…”
2. P1, L20: “basically” => “mainly”
3. P2, L2: “The stratospheric…” => “Stratospheric…”
4. P2, L4: “…(Park et al,. 2012), the stratosphere…”  =>  “…(Park et al,. 2012), stratosphere…”
5. P2, L23: “…even so for …” => “… even for…”
6. P3, L4: “…to Beijing.” => “…of Beijing”
7. P3, L6: “…recording the near …” => “… recording near …”
8. P4, L11: define WACCM with a reference.
9. P4, L16: place this definition and reference to WACCM in line 11.
10. P4, L18: “…above that is still taken…” = > “…above 50 km is taken …”
11. P4, L19: expand a bit on the Tikhonov equation. It is entered here without explaining any of the terms. Explain how a value of 50 was obtained.
12. P5, L7: “The HBR cell …” => “HBr cell …”
13. P5, L15: …”several less…” => “…several orders of magnitude less…”
14. P5, L16: this sentence would read better as; “Therefore, in the stratosphere the FTIR retrievals during the daytime are much larger than the a priori profile.”
15. P5, L19: “…have the sensitivity…” => “…have sensitivity…”
16. P5, L20: This is a little misleading the way this is written. Not all layers are sensitive to the stratosphere, since there is no information in the troposphere. A more correct way to put this is that there is sensitivity to NO in the layers in the stratosphere. Note also some sensitivity in the upper troposphere between 10 and 16km, particularly at Maido.
17. P6, L2: Presume this is the average dofs over the entire datasets?
18. P7, L9: “…to the HITRAN2016…” => “…to the HITRAN2016 linelist…”
19. P8, fig 4 caption: “…DOF equalling..” => “…DOF’s equal …”
20. P8, L4: “…estimated 13.5%...” => “…estimated to be 3.5%...”
21. P8, L8: “…less than that of NO…” =>  “ …less than the NO…”
22. P8, L9: “ …less …” => “smaller”
23. P9, L5: suggest this sentence reads “Due to photochemical reactions (Kondo et 5 al., 1990), a large diurnal variation of the stratospheric NO is expected.”
24. P9, L7: “…SZA of measurements.” =>  “…SZA of the measurements.”
25. P9, L7: “…2 order…” => “… 2^nd.”  There are a few other locations where this appears.
26. P9, L8: “…t is in a fraction of local hour).” =>  “…t is a fraction of the local hour).”
27. P9, L12: “…with the time.” =>  “…with time.”
28. P9, L18: “…formed NO…” =>  “… NO formed…”
29. P9, L20: “…stratosphere, then …” =>  “….stratosphere, so…”
30. P9, L23: “…and of 0.74…” =>  “…and 0.74…”
31. P10, error budget: what about inferring species? A solar model is used (but not mentioned as part of the retrieval strategy, for example table 1) so presumably this is part of the retrieved parameters. But does this solar model include both solar line strength and shift?
32. P11, fig 7 caption: “The R is the …”  =>  “R is the …”
33. P12, L1: “…t is in fraction of year…”  =>  “…t is fraction of the year…”
34. P12, L2: “…which is relative…” =>  “…is relative…”
35. P12, L10: “…on one hand…”  => “…on the one hand…”
36. P12, L29: “…both start measuring…” =>  “…both started measuring…”
37. P12, L34: “…smoothed with FTIR…” =>  “…smoothed with the FTIR…”
38. P13, L5: “…are similar observed…” => “…are similar as observed…”
39. P13, L9: “…The possible reason is that…”  => “…The possible reason for this difference is that…”
40. P14, figure 9: The key needs to be reasonably self-explanatory. The numbers and trends in the key should be in the figure caption. For example the black dot entry should read MIPAS daily means, and the number of points can go into the figure caption. Same comment for all the other entries. The colour coding is also not consistent between what is described in the caption and what appears on the graph. For example, the blue shadow for MIPAS is actually purple, the blue solid line for MIPAS is green, while the purple shadow for the FTIR is pink. This could be related to the way colours are displayed in the pdf reader.
41. P14, L2: “…which is corresponding…” =>  “…which corresponds…”
42. P15, figure 10 caption: “Scatter plots between…”  =>  “Scatter plots at Xianghe between…”
43. P15, figure 10 caption: a comment about the way this plot is presented and captioned. The explicit way of knowing that this figure represents Xianghe is the caption title, which is fine But the caption explanation should be more explicit about what the data is and where is from since there is more than one site.
44. P15, L8: “…slightly large…” =>  “…slightly larger…”
45. P15, L8: “It is because that the…” =>  “The reason for this increased correlation is …”
46. P15, L7-9: The underlying reason is the increased cross-relation between the tropospheric and stratosphere layers, due to the individual averaging kernels being broader.
47. P15, L11: why are there no tropospheric NO measurements in summer? This maybe explained later (high water?), but a reference could be placed here that this will be explained later in the paper.
48. P15, L12: would this normally be expressed as mean (std) is 1.4 (1.0) x 10^16, as it is in the abstract.
49. P16, figure 11 caption, last sentence: this colour is not yellow, more light green. Maybe this is a function of the pdf viewer?
50. P16, figure 12 caption: “…CO tropospheric partial columns.” => “CO tropospheric partial columns at Xianghe.”
51. P16, L2: “…combustion for…” => “…combustion from …”
52. P16, L4: individual => independent
53. P17, L25: depend => dependent