A new insight into the vertical differences in NO<sub>2</sub> heterogeneous reaction to produce HONO over inland and marginal seas

Xing, Chengzhi; Xu, Shiqi; Song, Yuhang; Liu, Cheng; Liu, Yuhan; Lu, Keding; Tan, Wei; Zhang, Chengxin; Hu, Qihou; Wang, Shanshan; Wu, Hongyu; Lin, Hua

doi:https://doi.org/10.5194/acp-23-5815-2023

Articles | Volume 23, issue 10

https://doi.org/10.5194/acp-23-5815-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-23-5815-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 10

Research article

|

26 May 2023

Research article |

| 26 May 2023

A new insight into the vertical differences in NO₂ heterogeneous reaction to produce HONO over inland and marginal seas

Chengzhi Xing, Shiqi Xu, Yuhang Song, Cheng Liu, Yuhan Liu, Keding Lu, Wei Tan, Chengxin Zhang, Qihou Hu, Shanshan Wang, Hongyu Wu, and Hua Lin

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CC1:
'Comment on acp-2022-638', Jörg Kleffmann, 09 Nov 2022

Comments to the manuscript by Xing et al.:
In the manuscript by Xing et al. MAX-DOAS measurements during ship cruises and on two land stations (inland and coast) were used to measure vertical gradients of HONO and NO₂ to identify potential source mechanisms. Gradient measurements are of significant importance to distinguish between near ground (e.g. direct emissions, heterogeneous NO₂ conversion, etc.) and volume sources (e.g. on particles) of HONO. Only when the vertical HONO structure is known, the impact of HONO on the oxidation capacity of the whole boundary layer can be described, in contrast to typical near surface measurements by in-situ instruments, which overweight the contribution of HONO. Also, when using a path averaging spectroscopic method the risk of overestimation of HONO levels by interferences and sampling artefacts in the instrument’s inlets are minimized. Thus, such measurements are of general high importance.
However, I could not follow all the evaluations and arguments in the manuscript caused by missing information. The following comments could be considered to improve the manuscript.

Major comments:
1) Section 2.1: Missing information to CAMS and SUST sites:
Besides the ship measurements, MAX-DOAS measurements were also performed in parallel in two stations, which were defined as “inland” (CAMS) and “coastal” (SUST). Here I am missing more information to both sites. Especially, where are they? E.g. for the Chinese Academy of Meteorological Science (CAMS) I found Beijing (?), which would be far away from the ship measurements and would make any comparison highly uncertain…

2) Sea- vs. land-oriented measurements:
The ship data was divided in sea- and land-oriented measurements. But isn’t that both sea data? To answer this question, two important information are missing: a) How far away were the ship tracks on average from the coastline? b) what is the typical distance for the light-path of the MAX-DOAS (only the horizontal vector is of importance)? I expect that the distance of the ship from the coast (some km?) was larger than the “horizontal view” of the instrument (horizontal distance between the average scattering point and the instrument). From my experience for Chinese conditions the visibility if often significantly smaller than 1 km… In this case the instrument is only evaluating sea influenced air masses and the observed differences reflect only some undefined horizontal gradient between sea and land, but not any “sea” of “land” data.

3) Direct HONO/NO_x emission ratio
In section 3.2. it seems that HONO/NO_x ratios from direct emission were determined by the measurement data for CAMS and SUST. However, it is unclear how this has been done? In the present study, only daytime data could be used (light source of the MAX-DOAS = sun…). But one filter to determine the HONO/NO_x ratio of direct emissions from field data - besides others - is to use only night-time data, caused by the fast photolysis of HONO!? In addition, because of strong vertical gradients and the vertical resolution of the MAX-DOAS the combined use of path averaged HONO and NO₂ data in comparison to in-situ NO ground data cannot be recommended (apples and oranges…). The method used is completely unclear and should be further explained. E.g. how was the direct emission ratio of 0.46% (line 216) of Sun et al. considered (“used to understand…”)?

4) Unrealistic HONO/NO_x data:
If the HONO/NOx ratio for direct emissions of 0.82 % (CAMS) and 0.79 % (SUST) are true, then the slopes of all HONO against NO₂data shown in Fig. 5 (a) 0.8 % for CAMS and b) 0.5 % for SUST) are not possible. Even if one assumes the absence of any NO in the atmosphere (very unreasonable) the slopes when using all data should be by definition larger than only the direct emission ratio!? Typically, that should be a few % for field data (cf. ratio of the average ship data of ca. 2.5 %, which I get from the data in lines 191-192) for which 0.8 % (lower limit during daytime, see below) may be direct emissions. But here for SUST all data show a lower HONO/NO₂ ratio (and the HONO/NO_x ratio would be even much lower…) than the direct emission ratio. Please check the data.
In addition, during daytime a measured HONO/NO_x ratio (e.g. from sharp plumes) will be lower than what is directly emitted. This can be explained by the different lifetimes of HONO (10-20 min during daytime) and NO₂ (typically some hours). Thus, depending on the time between emission and measurements the contribution of direct emitted HONO will decrease (this is the reason why the “night-time filter” is used to measure direct emission from field data…). For details I recommend the paper by Xue et al. (https://doi.org/10.5194/acp-22-3149-2022).

6) Unrealistic HONO/NO₂ gradient data:
In figures 9-11 vertical gradient data of the HONO/NO₂ ratio are shown. Here increasing ratios are observed with altitude, which is in contrast to most gradient data, which I know (cf. e.g. our gradient data on a 190 m tall tower, Kleffmann et al., 2003 doi: 10.1016/S1352-2310(03)00242-5). While this may be explained by any unusual chemistry over sea surfaces, the absolute numbers of the HONO/NO₂ at higher altitude of up to 45 % (see Fig. 10) are impossible, independent of how strong any HONO source – e.g. particle nitrate photolysis – may be. The photolysis of HONO is a source of NO. In a typical atmosphere for which [O₃]>[NO_x] this is quickly converted to NO₂. Since in higher layers in a well-mixed atmosphere a PSS can be assumed (far away from any direct sources) the maximum HONO/NO₂ ratio is given by the ratio of the lifetimes of both molecules. For HONO this is around 10 min at noon (check for J(HONO)), while for NO₂ this is mainly limited by its reaction with the OH radical during daytime (the Leighton chemistry will not play a role here). Assuming a high OH concentration of 10⁷ cm^-3 at 1 km altitude a lifetime of ca. 3 h can be calculated. Thus, a maximum HONO/NO₂ ratio of ca. 6 % should result under steady state conditions. If HONO is measured close to a source, e.g. in near ground measurements in a step vertical gradient, higher HONO/NO₂ ratios are possible (= no PSS…). But in a homogeneous mixed atmosphere at 1 km altitude (see figures 9-11) such high HONO/NO2 data is impossible. Please check.

Minor comments in the order of the manuscript:
Line 37-38: There are several “heterogeneous reactions of NO₂”. Here the authors should distinguish between slower nighttime conversion (NO₂+H₂O and NO₂+organic) and daytime sources (NO₂+organic + light, see Stemmler et al., 2006; or NO₂ +TiO₂+light = photocatalysis). Otherwise some arguments of the authors (with solar radiation, see below) are unclear.

Line 51-53, general comment to this section, but also to the author’s own evaluations: These simple correlation studies always bear the risk of a misinterpretation of the results. Typically, trace gases which are emitted or formed near to the ground will anyhow correlate caused by the variable mixing layer height. The is mainly modulated by diurnal surface temperature variation which has also an effect on the relative humidity. Thus, e.g. at the end of the night the temperature and mixing height are low, while the relative humidity is high. Caused by the resulting high S/V ratio under these conditions, heterogeneous HONO formation is faster and the HONO/NO_x ratio will correlate with the humidity, without any necessary mechanistic link (see also correlation of Radon with HONO…). Also, often at very high humidity the HONO/NO_x ratio is again decreasing with humidity. This is typically explained by uptake on very humid surfaces. However, the highest relative humidity is often observed close before sunrise, when direct emissions start to increase. Thus, the high HONO/NO_x air masses from slow nighttime sources (typically 5 %) are “diluted” by fresh low HONO/NO_x emissions (around 1%), leading to the decreasing HONO/NO_x ratios at high humidity. Thus, the authors should highlight (and later consider for their own evaluation…) that simple correlation analysis may lead to artificial correlations and misleading conclusions.

Line 77-85: With respect to the main topic of the manuscript, I would expect a more extended summary of the existing gradient data (from towers, and MAX-DOAS), which is normally very different to the present results (see major comment 6).

Line 187-189: This sentence could make sense only if a photolytic NO₂ conversion process is considered (see above). However, even for a photolytic NO₂ conversion process which was found to correlate with J(NO₂) in lab studies (see Stemmler et al., 2006), the steady state HONO/NO₂ ratio would not change with variable solar radiation, since both, J(HONO) (sink) and J(NO₂) (source) show a linear correlation. Thus, the argument is not valid.

Lines 191-192 and 205: Here very different HONO/NO₂ ratios are specified for the same (?) ship data? From the data in lines 191-192 I get values of 2.7 % and 2.4 % (“total averaged”), while in line 205 45 % are mentioned for the “average value”? Check data and/or explain differences.

Line 202: should be “high HONO concentration”. A production rate (dHONO/dt) was not determined and you may have a small production rate (slope) at high HONO.

Line 206-207: Check again the argument (see above, sources and sink scale with radiation…).

Section 3.2.1: Check whether the “turning points” (especially the two in Fig. 6c) are significant or just scatter of the data? In addition, possible “artificial correlations” should be discussed, see above.
And can you explain, why only the “six highest values” are shown in Fig. 6 (red data) and not the mean/median? Is that representative or are here only outliers shown?

Line 245, 246, 251: Here continuously increasing or decreasing data is shown and the highest value are specified as “peak”. However, the “peak values” were not determined and could be even at lower or higher temperatures…

Paragraph lines 282-295/ figures 10 and 11: What is the difference between both figures? Seems to be the same? Define two cases?

Line 315: Where is that HONO peak at 12:15 in Figure 12c? I see a stronger peak at ca. 14:15…?

Line 330-331: The two RH and especially the two T values are not very different to allow any conclusions to the mechanism.

Line 343-344, Fig. 15: Not the NO₂ concentration is increasing during this period (see color code), but the layer is getting thicker.

Line 347-348. The peaks in HONO at ca. 9:45, 11:00, 11:45 and 12:30 in Fig. 15 are anticorrelated to NO₂ (in contrast to the statement…), which is very unusual? Check data and sentence.

Line 375: Should be “emission ratio”.

Fig. 1: The data shown seems to be not “typical”. The DSCDs in the figure are factors higher than the data described in section 3.1?

Figure 3. Check the HONO/NO₂ data. I get 0.027 and 0.024 using the HONO (0.23 /0.27) and NO₂ (8.46/11.31) data?

Figure 6: please show the red/right y-axis scaling in all figures (will be different in a) and b)).

Figure cations 10 and 11. Is “Sea” the average data or “sea/land oriented data”?

Citation: https://doi.org/10.5194/acp-2022-638-CC1
- AC1: 'Reply on CC1', Chengzhi Xing, 25 Jan 2023
  
  The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-638/acp-2022-638-AC1-supplement.pdf
  
  Citation: https://doi.org/10.5194/acp-2022-638-AC1
RC1:
'Comment on acp-2022-638', Anonymous Referee #1, 11 Nov 2022
Heterogeneous reaction of NO₂ on wet surfaces is an important source of HONO. However, there are still many uncertainties in the research on the mechanism of the heterogeneous reaction of NO₂ to produce HONO, and a complete consensus has not yet been reached in the scientific research community. Pseudo-steady-state calculations and model simulations also show that HONO levels will be greatly underestimated by considering only homogeneous chemical reactions. At present, the assessment of the contribution of the heterogeneous reaction of NO₂ to HONO in the vertical boundary layer has not been fully determined, which hinders the in-depth understanding of the distribution characteristics of tropospheric HONO, the transformation and formation process and its environmental effects. In addition, the research on HONO and its precursors in coastal and offshore scenarios is not sufficient, resulting in a lack of understanding of the ocean-atmospheric nitrogen cycle and the sea-land-atmosphere interaction.

Xing et al. can not only provide data support for the improvement of atmospheric chemistry models, but also provide new insights for exploring the vertical sources of HONO on land and sea and the effect of photolysis on the oxidation capacity of the upper atmosphere, but also for the prevention and control of atmospheric composite pollution and PM_2.5. The synergistic control with O₃ provides new scientific basis and clues. I suggest publication in ACP after minor revision. The detailed comments are as follows:

In this study, the uncertainty evaluation is imperfect. I suggest the authors to add a section or even in the supplement to explain the uncertainties of data or how trustworthy of the presented data in this manuscript.

The authors should explain the meaning of this works clearly. Moreover, I suggest to shorten the abstract, which is quite long and contains too many details.

The methodology section is too simple, especially in the vertical profile inversion module. Authors should provide detailed descriptions even in supplement.

Section 3.4: The case study is too subjective. The authors should add detailed reasons for the case selection. Furthermore, section 3.4.2 lacks of sufficient proof.

The conclusion is too long and should be shorten. Moreover, the implication the ship-based observation should be also added.
Citation: https://doi.org/10.5194/acp-2022-638-RC1
- AC2: 'Reply on RC1', Chengzhi Xing, 25 Jan 2023
  
  The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-638/acp-2022-638-AC2-supplement.pdf
  
  Citation: https://doi.org/10.5194/acp-2022-638-AC2
RC2:
'Comment on acp-2022-638', Anonymous Referee #2, 29 Nov 2022
Summary

A better understanding of the sources and formation mechanisms of HONO is important for understanding troposphere oxidation and processes of secondary pollution. Previous research has focused on the near-surface layer such that there is insufficient literature measuring heterogeneous formation of HONO in the vertical profile. This study uses MAX-DOAS to study the vertical distributions of HONO and its sources over the sea along a Chinese coastline and at coastal stations. Retrievals of vertical profiles of aerosol, NO2 and HONO allow the examination of the differences in heterogeneous production of HONO in sea versus inland cases.

This work can provide important new information on the variation of sources of HONO in the vertical profile within the lower troposphere. However, the evaluation of data uncertainty is incomplete and hinders the use of the study’s findings. The detailed comments to be considered are below:

Major Comments

There is general lack of uncertainties or error estimates presented with the measurements throughout, which makes the significance of the findings and conclusions uncertain. Any comparison of averages should include the standard deviations (ex. the VCDs on line 6 and concentrations on line 9). The results and discussion section requires discussion of which results are statistically significant and, therefore, an important contribution to the knowledge of the field. Presenting the uncertainties associated with the retrieved vertical profiles of NO2 and HONO is also required to draw significant conclusions about trends (Lines 269 to 281 & figure 9). The optimal estimation method should have produced some estimate of error when retrieving the vertical profiles. These errors bars should be included in the figures. Retrieval uncertainty is particularly important for the HONO/NO2 ratios due to error propagation. For example, since the sensitivity of the MAX-DOAS retrievals tend to decrease with increasing altitude, the ratio values at higher altitudes in the profile may be a function of the chosen a-priori values rather than the true state of the atmosphere, and therefore cannot be interpreted. In general, a discussion should be included on how the changing MAX-DOAS sensitivity with altitude impacts the shape and magnitude of the retrievals compared to the true atmosphere (either the methodology or results sections). Otherwise the readers might assume that the MAX-DOAS vertical profiles are more accurate at higher elevations than is the case (versus, for example, the accuracy level of lidar vertical profiles of aerosol extinction). An example of a typical averaging kernel from the optimal estimation retrieval should thus be provided (ex. in the supplemental). Finally, what sensitivity testing was conducted in terms of the effect on the chosen a-priori shape on the shape of the retrieved profiles?

The use of English needs some improvement. Typos and grammatical errors, such as missing the words “that” and “the” in many sentences, reduces overall clarity. The manuscript would benefit from professional English editing.

Minor Comments

Lines 16 to 19. For improved English, these sentences should use the format “the HONO/NO2 ratio was observed to decrease with increasing temperature…”

Lines 29-30. Under land or sea conditions?

Lines 34-35. Amend to “… nitrate amines that pose a threat to human health”.

Line 37. Suggest listing the important/known HONO formation reactions, similar to the introduction in the Wen et al. (2019) referenced.

Lines 39-40. Should this be “there are sources of HONO that are poorly understood”? Rewrite for clarity.

Lines 68 – 69. Are “favourable weather conditions” sea breeze conditions? Otherwise, what does “favourable” mean here?

Line 82. Add “above surface” after 120 m.

Lines 145 – 152. Suggest adding more detail about the optimal estimation method. For example, that the aerosol vertical profiles are retrieved from the O4 DSCDs, which are then used as model inputs for retrieving trace gas vertical profiles. What was the magnitude of the a priori for the aerosol and trace gas retrievals? How many minutes of measurements were included in the retrieval of one profile?

Lines 160 – 161. It says in section 3.1 that the radiative transfer model SCIATRAN was used to convert SCDs of NO2 and HONO to VCDs, but why were the vertical profiles retrieved using the optimal estimation method not used to calculate VCDs? This appears to be duplication of work. If there is a lack of confidence in the vertical profiles from the optimal estimation method, this should be explained. Were the VCDs calculated using the two different methods compared? If so, please include in the supplemental and justify the methodological choice.

Line 172. Suggest changing “elevated” to “enhanced” to make it clear that the hotspots were much greater than background as opposed to elevated above the surface (i.e. “lifted”).

Lines 171 to 182. A bar chart comparing the averaged NO2 and HONO (with standard deviations) in the five areas will be useful for the reader in terms of observing differences in the distributions described in the text. Box and whisker plots might also be a good choice since they provide more details about outliers.

Line 213. What is meant by “navigation areas”?

Lines 210 to 11. More details about these stations are required. Where they located (ex. latitude and longitude coordinates). What are the characteristics of the stations? For example, local pollution sources, topography, prevailing meteorological conditions, etc.

Lines 216 to 222. Much more detail is needed in terms of how the emission ratios were determined (i.e. in the methodology section). Simply citing the literature is not sufficient.

Line 223. Since later sections show how meteorological variables impact the HONO/NO2 relationship, it would be helpful to add visualise the impact on these scatterplots using coloured marker points. For example, you could provide versions of these plots where each point has a color corresponding to the temperature. These plots may help to explain some of the outliers that are reducing the R values.

Line 230. Please explain and justify this methodological choice in more detail.

Line 231. Define “turning points” for the reader.

Lines 243 to 244. Please explain and justify the methodological choice of using the average of the six highest values.

Line 252. Does “landing winds” mean a land breeze?

Lines 257-260. Given that the R squared of the inland correlation is so small (<0.1), the fitted slope cannot be reliably interpreted (has no statistically significant meeting).

Lines 263 to 266. Showing the averages and standard deviations of the ratios and aerosol extinctions in a bar chart, perhaps in the supplementary section, would help the reader. This comparison will also help to determine whether the average values are statistically significantly different based on the standard deviations, which is important to justify your conclusions.

Line 373. The sentence is vague. Consider revising to something like, “when peak AOD and NO2 conditions were observed, enhanced HONO were observed, but the reverse was not always the case.”

Lines 374 to 376. Consider changing “to remove the primary HONO source” to “to quantify the contribution of the primary HONO source to the total production of HONO.”

Line 552. Figure 12 c). Suggest reducing the maximum value on the colour bar for the HONO concentrations to make the enhanced periods easier to see.
Citation: https://doi.org/10.5194/acp-2022-638-RC2
- AC3: 'Reply on RC2', Chengzhi Xing, 25 Jan 2023
  
  The comment was uploaded in the form of a supplement: https://acp.copernicus.org/preprints/acp-2022-638/acp-2022-638-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/acp-2022-638-AC3

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload

AR by Chengzhi Xing on behalf of the Authors (25 Jan 2023) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (01 Feb 2023) by John Liggio

RR by Anonymous Referee #2 (22 Mar 2023)

Suggestions for revision or reasons for rejection

I would like to congratulations the authors on doing a good job integrating and responding to the reviewers’ comments (a non-trivial effort!).

Kleffmann #Major Comment 3)
- Line 276: To clarify that the deltaHONO/deltaNOX emission ratio used was the value determined by Sun et al. (2020), and not derived from measurements during the study using the method by Sun et al. (2020) (potentially implied), I suggest you change the wording to something like: “we used the averaged emission ratio of X derived by Sun et al. (2020) from measurements of fresh ship plumes over the East China Sea…”
-It is still unclear what you mean by “to understand the primary source.” Do you mean that, instead of calculating this ratio from your study data, you are assuming the value from Sun et al. (2020) can be applied to your study?

#Major Comment 5)
Thanks for providing Figure R6. The averaging kernels look sound and typical of MAX-DOAS retrievals of NO2 and HONO. Some observations about the shown averaging kernels below:
-For low aerosol conditions : by altitudes of 600 m, the retrieval profile derives only ~30% information from the true atmospheric state compared to the a-priori for NO2 and slightly less for HONO retrievals. For 800 m and above, little information is derived from the true atmospheric state compared to the a-priori (<10% for aerosol and NO2; 20% for HONO). Therefore, profile concentrations retrieved above 800 m will mostly reflect the a-priori rather than the atmospheric state. This lack of sensitivity can results in HONO/NO2 ratios with large uncertainties for altitudes ~600 m +.
-High aerosol: little information at 600 m is derived from the true atmosphere for the HONO retrievals (approximately 10%) compared to the the NO2 retrievals (approximately 70%). This suggests that the HONO retrievals contain little atmospheric information for ~>600 m and the HONO/NO2 ratios have high uncertainty due to error/retrieved values tending towards the a priori.
-Also note the differing shapes of the averaging kernels between the NO2 and HONO retrievals for the same heights (ex. see 0.6 km for high aerosol case). These differences mean that the retrievals smooths the atmospheric data differently for the retrieval for NO2 vs. HONO, adding error to HONO/NO2 ratios at a discrete height (not strictly apples-apples comparison).
- Regarding the unexpectedly large values of HONO/NO2 ratio above 500 m (not consistent with the expected chemistry) in Fig 10 d) for ship-based conditions: based on the a-priori profiles for NO2 and HONO shown in Figure S4, the HONO/NO2 from the a-priori profiles is ~ 0.4. At higher altitudes, where the retrieval contains relatively little information from the true atmosphere, the HONO/NO2 ratio likely tend towards ~0.4. The HONO/NO2 ratios appear to be within expected values of <0.1 until above 600m, where retrievals, especially for HONO, tending towards the a-priori is likely artificially increasing the HONO/NO2 ratio.
-Therefore, the retrieved concentrations at altitudes above 600 m, especially for HONO, must be interpreted very carefully in the discussion and the HONO/NO2 ratio are likely invalid for interpretation, containing too little atmospheric information from at least the numerator such that large uncertainty is propagated into the ratio while error estimation by the retrieval algorithm is probably underestimated. In Figs. 8-10, the error bars on the HONO/NO2 ratios are quite large > 600 m and are probably even larger in reality (could easily be 100% for some retrievals) given the above discussion.
-My suggestion is to either: 1) exclude HONO/NO2 ratios above ~ 600 m in the figures and the discussion because of the reasons discussed above unless the averaging kernels suggest accurate retrievals at higher altitudes for the particular retrieval OR 2) make the above concepts and sources of uncertainty/ error clear to the reader when discussing the ratios Figs. 8-10, especially when the ratios are greater than expected.
-Specific example: Section 3.3 lines 345-351 & 357-358: Ratios of HONO/NO2 above ~500m should be interpreted with caution. While you can retain the hypothesis about generation rates of HONO (for Fig. 9(e), for example), ensure the potential that this result is due to uncertainties is made clear to the reader. Alternatively, remove discussions/conclusions for HONO/NO2 trends and comparisons for altitudes >600m.
- The authors could test the impact of a-priori on HONO/NO2 ratios and add this to the supplemental by retrieving HONO profiles using an a-priori that decreases more rapidly with altitude than the one already. However, to prevent having to do more retrievals, I believe adding the above discussion points and explanations to the reader are sufficient.
- The authors could also state in section “2.4 Error analysis” that errors are likely much higher than those calculated and shown in Table 3 at higher altitudes, particularly above 600 m.
-The authors may want to note for the reader in the methodology or error analysis sections that multiple vertical profile shapes can result in the same VCD (same degree of error minimization in the retrieval), such that VCDs have much smaller error than the concentration at a particular altitude in a retrieved vertical profile. When it was stated on page 30 that “the relative change was within 30%” for different scale heights for the a-priori profile, I presume that was for the VCD rather than concentrations at particular heights.
-Lines 368-369: suggest changing to “sensitivity of the MAX-DOAS retrievals to the true atmospheric state increases with decreasing altitudes and vertical profiles under 500 m have the greatest reliably (Figure S10).
-Figure S10: Please explain briefly to the reader what averaging kernels are in the Figure caption.
-Section 3.4.3 Line 424: to increase confidence in the HONO profiles between 0.5-1.0 km, suggest adding the respective averaging kernels to the supplement.

Referee #2
#Major Comment 1)
The authors still need to include the standard deviation values for any average value from their dataset throughout the manuscript before publication (ex. average VCDs in lines 228-229).

#Major Comment 2)
Lines 166-167 suggest stating that the retrievals were especially sensitive for layers within 0-500 m, rather than 0-1.5 km (especially if referring to HONO).
I support with the authors’ use of an exponentially decreasing a-priori profile and agree a challenge of MAX-DOAS retrievals is choosing the “optimal” a-priori profile.

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ED: Publish as is (03 May 2023) by John Liggio

AR by Chengzhi Xing on behalf of the Authors (04 May 2023) Manuscript

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High RH could contribute to the secondary formation of HONO in the sea atmosphere. High temperature could promote the formation of HONO from NO₂ heterogeneous reactions in the sea and coastal atmosphere. The aerosol surface plays a more important role during the above process in coastal and sea cases. The generation rate of HONO from the NO₂ heterogeneous reaction in the sea cases is larger than that in inland cases in higher atmospheric layers above 600 m.

A new insight into the vertical differences in NO2 heterogeneous reaction to produce HONO over inland and marginal seas

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A new insight into the vertical differences in NO₂ heterogeneous reaction to produce HONO over inland and marginal seas