Review of “The impact of atmospheric motion on source-specific black carbon and the induced direct radiative effect over a river-valley region” by Liu et al.

In this paper, the authors describe the impact of different types of atmospheric transport and motion scales, from local to regional, on the black carbon concentrations in a city in China. I think the paper presents a few interesting results with implications also for the radiative forcing of black carbon particles. Therefore, I would recommend publications after a few aspects are clarified and the comments below are addressed.

General comment

• The site location should be described in more detail, and also earlier on. Some more comments on this issue are below.
• The English grammar and style could be quite significantly improved. A few examples of some issues are provided in the specific comments below, but many more instances are present in the paper. Maybe some editorial work by a native-speaking scientist could help improve the language and therefore clarity.
• The origin of the biomass burning BC is not well described or discussed. Is this agricultural biomass burning, wildfires, or residential biomass burning? Something else?
• The literature citations are a bit scarce and somewhat biased. A broader representation of the work published in the literature and relevant to the authors’ work outside of their own work, would help.
• Maybe is my lack of familiarity with some of these aspects, but some of the data analysis methods (e.g., SOM, but not only) are not described in sufficient detail. The authors refer to existing literature, but a brief description of the methods' workings, input, outputs, limitations, etc. would help improve the clarity and broaden the audience of the paper.

Specific comments

Abstract:

• “Black carbon (BC) has a strong light absorption ability and is known as the second strongest light-absorbing substance in the atmosphere after CO2” This is debatable.
• What does model refer to in “aethalometer model”?
• “chemical data and optical data” what kind of data?
• “The derived AAEs” over what wavelength range?
• “four featured atmospheric motions categories” what the four categories are remains a mystery until later, please provide a brief description here because the abstract should be self-contained.
• “The trajectory clusters” what trajectories? How were those determined?
• Lines 30-31: I don’t understand the sentence “This study revealed the disproportional change between BC mass concentration and its DRE.”
• Line 32: “It highlights…” what does “it” refer to? In general, this closing sentence reads awkward, and I would suggest rewording it.

Introduction:

• Light absorbing or agent with positive radiative forcing? The two whings are linked but not the same.
• Line 55: remove “at” before “to”
• Line 57: multiply -> multiple
• Line 62: Why the aerosol concentration controls the local scale motion?
• Line 64: diffuse -> disperse?
• Line 65: “decides” seems more to belong to an intelligent entity. Maybe “determines”
• Line 72: “river valley city” comes a bit out of the blue here, it might be good to provide a sentence with some background, like the general location, etc., even if that’s then discussed in detail in the method section. Is the city specifically Baoji?
• Line 75: why the albedo makes the solar radiation uneven? Do they mean the reflected radiation? In general, I find this sentence awkward and unclear.
• The sentence starting on line 77 is also awkward and should be reworded.
• Line 80: eBC appears here without having been defined as equivalent BC. It has been defined only later, but it should be defined at its first appearance.
• Line 81: I believe the authors meant: “the contributions of fossil fuel combustion and biomass burning to eBC concentrations”

Method

• Line 88: Guanzhong Plain is where the river-valley city of Baoji is located, I guess? It would be nice to say so right at the beginning.
• Section 2.1: a map of the region I think would help as figure 1.
• Line 94: dense population, provide some numbers such as the total population, and population density.
• Section 2.5 is quite confusing.
• Line 175: A ratio indicates a difference? That is confusing. Also, R is defined in 13 not as the ratio of L and S but as the ratio of the difference between S and L and S itself. Or is this a different R?
• Line 189: Again, if equation 13 is correct, then R is not the ratio of L to S but 1 – the ratio of L to S. Same for line 191 (which seems a repetition anyway).
• Lines 192-193: this seems a bit of a circular argument (a tautology).
• Line 207: provide a citation.

Results and discussion

• Line 261: contain -> include
• Line 222: what is the default ratio in the model? And what model? OPAC?
• Line 230: at -> of?
• Lines 238-239: Provide some more background or at least some references
• Line283: variations… varied… rephrase.
• Lines 293 – 294. Remove “New para here”
• Line 295: why did the biomass burning increase after 6 pm? Is it indoor biomass burning for cooking or heating, or is it some other biomass burning?
• Figure 3, caption: Explain the meaning of the gray and yellow areas even if that’s explained in the text.
• Line 344: can one try to verify this with the backtrajectory analysis, or satellite products. etc.
• Line 350: I would suggest briefly summarizing what the angle distance clustering method is and how it works even if that’s explained in detail in the cited paper.
• Lines 360 – 362: Rephrase this sentence, there are several awkward readability issues.
• Line 360: remove “at” before “in”
• Paragraph starting at line 405, specifically lines 411- 413: this is consistent with the higher MAC values.
• Caption of figure 5: explain what the different shadings represent. Also, x-axis label number four probably should be “DREeBCfossil, TOA” not “DREeBCbiomass, TOA”. It could be interesting to add another two panels with the equivalent calculations but in terms of efficiency to make more clear what is discussed in words in the paper.

Atmospheric Chemistry and Physics

Manuscript ID: acp-2022-26

Title: The impact of atmospheric motion on source-specific black carbon and the induced direct radiative effect over a river-valley region

Comments to Editor:

Dear Editor,



I apologize for the late feedback. More comments were needed on the manuscript and supplementary material than I had thought.



Best regards

General comments:

This manuscript describes how Black Carbon concentrations, measured over a little more than a month in winter 2018 together with other chemical species in PM_2.5 in a Chinese city nestled at the bottom of a valley, vary with different transport regimes and motion scales (from local to regional).

The topic of the manuscript fits within the scope of the journal. The methodology should be described more precisely to build confidence in the results. The discussion section could be strengthened by comparing this work with other studies in similar topographic conditions.

The writing should be improved, I have suggested a few technical corrections in a specific section at the end.

Specific comments:

L30: What type of “change” between a mass concentration and a radiative effect is expected? I am not sure the word “change” conveys your meaning.

L37-38: “the second strongest light-absorbing substance in the atmosphere after CO2”. This wording is confusing since it seems an intrinsic property of BC whatever its concentration level. Besides it is clearly related to (1) its climate forcing ability and (2) human emissions only, by Bond et al. (2013) which state that “We estimate that black carbon, with a total climate forcing of +1.1 W m⁻², is the second most important human emission in terms of its climate forcing in the present-day atmosphere; only carbon dioxide is estimated to have a greater forcing.” (abstract) or “Our best estimate of black carbon forcing ranks it as the second most important individual climate-warming agent after carbon dioxide” (in 1.2.12 Policy implications). This sentence should thus be revised accordingly.

L60: “scale (it is atmosphere phenomena) ranges”. I do not understand what the mention in brackets refers to?!

L62: I do not understand how an atmospheric dynamic feature (the local scale of motion) is eventually controlled by the concentration levels of BC?! Besides the land roughness, it can be influenced by thermals, turbulence, etc.

L72-79: The authors mention the specific case of atmospheric dynamics in the context of a valley site surrounded by mountains. I am surprised not to find a word about temperature inversions which are very common in winter in such environments and have a tremendous impact on trapping pollution in valleys. See for instance Glojek et al. (2022), https://doi.org/10.5194/acp-22-5577-2022.

L87: The description of the research site and its surroundings is too brief. No mention of any altitude (site, surrounding mountains), which is a crucial parameter. The authors should provide a more detailed map of the city and the main local expected sources of Black Carbon (highway, residential areas, industries, etc.), as well as the 12 monitoring stations mentioned later in the text. It would also be helpful to know about the local wind rose over the different seasons, as well as basic meteorological data (temperature, RH profiles; precipitation patterns).

L101: The time resolution of AE33 aethalometers can either be 1 min or 1 s. Do you mean you used 5-min averages of the 1-min data?

L105-106: What type of quartz filter was used? The correction factor is dependent on the filter model.

L133: What is the spatial resolution of the GDAS meteorological data?

L162: The PMF methodology is described in section 2.3 for its classical use with mass concentrations of chemical species. Here it is used for optical source apportionment and therefore it should be explained how (concentrations are being replaced by what?) as well as the uncertainty calculation in that case.

L184: Is equation 13 correct? Both L175 and L188-189 describe R as the ratio between L and S but this does not correspond to the expression.

L206: What is the time resolution of the three sets of data? Are you using hourly averages?

L303-318: I would suggest to include the four different average values (L(bj), S(bj), R(bj) and R(std)) for the four motion categories in Table 1 as well, and not repeat all the values in this paragraph but rather focus on the comparison and the interpretation.

L341-344: Are emission inventories available to support the assumption that eBC from biomass burning is more regional then eBC from fossil fuel combustion? L388: A similar conclusion as above is reached here using the backtrajectory cluster analysis.

Non-parametric wind regression plots on these two variables could also be informative to assess the local vs. regional influence. See for instance:

Gu et al. https://www.sciencedirect.com/science/article/pii/S0160412019342369

or Pandey et al.: https://link.springer.com/article/10.1007/s10661-022-09879-9

Supplementary Information

Figure S5: eBC(diesel) is actually EC from the PMF factor attributed to diesel vehicular emissions if I understand correctly what is written in the main text (L248). I do not think it should be considered equivalent to an eBC(diesel) which is confusing with eBC(fossil).

Figure S8: The caption is not very informative. Do L24h and S24h correspond to L(bj) and R(bj) mentioned in the main text. Being not familiar with the SOM approach, it is hard to figure out what this represents and how to interpret it.

Technical corrections (list non-exhaustive):

L32: “It highlights”. Do you mean “This study emphasizes the fact that”? (or something along that line)

L54: “Local concentrations of BC are”

L55: “predictable at to some degree”. Delete “at”.

L56: “the concentration of pollutants follows”

L57: “multiple” instead of “multiply”

L76: “it can play”

L78: “to converge”

L80: “fascinated”. Maybe too strong a word? May I suggest “keen on studying” instead. “eBCs” not defined.

L92-93: “located at the furthest west”

L93: replace “suffers” by “suffering from”

L107: “Aurora”

L151: “deconvolved” rather than “separated”

L171: “different scales”

L230: “minus”

L235: “was run”

L236: “2-factor solution (…) 7-factor solution (…) 4-factor solution” + L237, L239

L279: “were calculated”

L282-283: “Their diurnal variations showed varied”. Please consider revising.

L282, 284: “diel” instead of “diurnal”

L293: “New para here” should be deleted.

L331: rather “clean” instead of “clear”.

L333: “were carried”

L360-362: Consider revising this sentence: “emissions at in” (delete “at”); “(~75%) of the total population of Baoji)” can be replaced by “(that is to say 75%)”; “distributed located”, pick only one.

L432: “outweighed the regional-scale motion”

L436: “found to be raised”

L717 : Figure 1 | x-axis title: “Pabs” instead of “babs”

L721: “diurnal” should be replaced by “diel” (24-hour period). At the least, standard deviations could be added for each hourly-averaged point; otherwise each point could be replaced by a box and whiskers that better show the dispersion of the raw data.

L724: Figure 3 caption should explain what the different marker colors and the shaded areas represent.

L731: Figure 5a | The 4^th box and whisker plot (blue) should be labelled “fossil” and not “biomass” on the x-axis.

Supplementary Information

Table S2 would look better if numbers were aligned with column titles.

Figure S1: Add a scale on both maps. Topography should be indicated on the closer range map.

Figure S2 caption: "the modelled b_abs(500 nm) (respectively, SSA) and the observed b_abs(520 nm) (resp. SSA)". Right now, it reads like a ratio of the two parameters.

Figures S4, S5 and S6: What does each point represent? (daily average, other?)

Figure S9: “diurnal” should be replaced by “diel” (24-hour period). At the least, standard deviations could be added for each hourly-averaged point; otherwise each point could be replaced by a box and whisker that better shows the dispersion of the raw data.