From the journal Environmental Science: Atmospheres Peer review history

21-Jun-2022

Dear Dr Permar:

Manuscript ID: EA-ART-06-2022-000063
TITLE: Atmospheric OH reactivity in the western United States determined from comprehensive gas-phase measurements during WE-CAN

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************

Reviewer 1

Large comments:
Why was GFAS selected as representative of what’s used in GEOS-Chem? It would be interesting to add a short write up of how the other major fire emissions inventories handle VOCs and how similar/dissimilar they are. Ah, you get there on line 484. Perhaps add slightly more details on this (e.g., which other inventories you checked).
Is there a reason you didn’t look at DC3 or discuss it at all? They made OHR measurements and sampled smoke, clean environments, etc., and you mention FIREX and ATom but not DC3.

Small comments:
Reorder line 36 so that it’s more logical: NOx, then VOCs, then O3, then SOA.
Lines 79-80, provide citations for the different regimes mentioned.
In Figure 1, is PAN even plotted? I don’t see it anywhere. Perhaps don’t include in legend.
I like Figure 2. Nice job!
Line 582: missing “of” - the bulk “of” VOC OH

Reviewer 2

Please see my review in the attached pdf.

We thank both reviewers for their positive feedback and helpful comments, which we believe have strengthened the revised manuscript in many ways. In the point-by-point response below, the reviewer’s remarks are in blue, and our responses are in black.


Referee: 1
Large comments:
Why was GFAS selected as representative of what’s used in GEOS-Chem? It would be interesting to add a short write up of how the other major fire emissions inventories handle VOCs and how similar/dissimilar they are. Ah, you get there on line 484. Perhaps add slightly more details on this (e.g., which other inventories you checked).

This is a good suggestion and we have clarified our choice of the GFAS inventory along with the scope of this analysis in Section 3.4. Specifically, using different emissions inventories has little impact on the results because they all use similar emission ratios and consequently estimate similar emissions for the 21 implemented species. Additionally, the number of VOCs available in the emission inventory does not affect our analysis because we are only comparing the 21 species implemented for biomass burning in GEOS-Chem. The discussion then, is to highlight that GEOS-Chem, as an example of CTMs, misses a significant amount of reactivity in fire emissions mostly due to the unmodelled VOCs. Consequently, even if the BB emission inventories are correct, those unmodelled VOCs could account for 50 % missing OHR.

Is there a reason you didn’t look at DC3 or discuss it at all? They made OHR measurements and sampled smoke, clean environments, etc., and you mention FIREX and ATom but not DC3.

Thank you for the suggestion to add DC3 to our discussion. We have included comparisons to the total measured OHR during DC3 along with the different portions of CO, CH4, and VOCs between these studies to the discussion of the free troposphere of section 3.1.

Small comments:
Reorder line 36 so that it’s more logical: NOx, then VOCs, then O3, then SOA.

Line 36 has been reordered as suggested.

Lines 79-80, provide citations for the different regimes mentioned.

We have added citation for the different regimes.

In Figure 1, is PAN even plotted? I don’t see it anywhere. Perhaps don’t include in legend.

PAN was included in the original figure but makes up less than 0.01 % of the tOHR. We have removed PAN as a separate species in Figure 1 and Figure S2. Additionally, we have added the following sentence at the beginning of Section 3:

“Similarly, PAN was found to account for < 0.01 % (range 7x10-5 – 2x10-3 s-1) of the tOHR in all environments in this work and is consequently not treated separately in our analysis.”

I like Figure 2. Nice job!

Thank you!

Line 582: missing “of” - the bulk “of” VOC OH

Done.

Referee: 2
Review of Permar et al., 2022
The authors use WE-CAN observations to determine the contribution of fire VOCs to calculated OH reactivity, and compare to the clean free troposphere, descents into Boise, Idaho, and aged fire emissions. The authors find that models should include biomass burning emissions/chemistry for furan-containing species, butadienes, and monoterpenes. This paper provides an important perspective on how models should treat fire emissions and furthers our understanding of the VOCs that drive OH reactivity. After the major revisions described below, this paper will be a strong contribution to Environmental Science: Atmospheres.

Major comments:
The authors should address the other oxidants that may be important in fire plumes, such as ozone and NO3 (even during the day – https://acp.copernicus.org/articles/21/16293/2021/). This can be either added to the discussion in the text, although I would strongly consider calculated the important species to ozone and NO3 reactivity.

This is a good suggestion. In the introduction (Line 38), we have added that NO3 and O3 are also important oxidants for phenolics, alkenes, and terpenes in wildfire plumes. As for calculating the important species for NO3 and O3 reactivity, we feel that Decker et al. (2019) sufficiently demonstrates that phenolics are the main species with competitive NO3 oxidation, while O3 is a competitive oxidant for alkenes and terpenes. We do not have reason to believe that our results would be any different. Instead, this work uses OH reactivity as a tool to explore how well recently identified and quantified species are represented in the Master Chemical Mechanism and GEOS-Chem. Additionally, many less commonly measured species do not have well constrained rate constants for their reaction with NO3 and O3, likely making calculated reactivities highly uncertain.

The authors also need to better describe their F0AM modeling.

Thank you for the suggestion. We have added additional detail to Section 2.5 about how F0AM was initialized and run in this work. Importantly, the original manuscript omitted that we used the laboratory derived fractional contribution of isomers to the total PTR-ToF-MS ions signal to estimate mixing ratios for individual VOCs initialized in the model. For example, the total m/z 59.05 mixing ratio is multiplied by 83 % to get only the acetone contribution for model initialization. Additionally, we have added that “physical parameters such as photolysis frequencies, temperature, and pressure were constrained to measured values at each model step while CO observations were used to derive a plume dilution correction factor”. Initial values remain listed in Table S3 with further model detail available in Peng et al. (2021).

The authors should discuss how the results from their previous work of disagreements between the PTRMS and other instruments (Permar et al., 2021) impact their findings.

Thank you for catching this important detail, as we originally did not discuss how we addressed this in text. There are five species important to the OHR that have notable disagreement between the PTR-ToF-MS and other instruments: isoprene, propene, furan, methyl furans, and monoterpenes. We have added the following paragraph in section 2.1 to discuss how we minimized their error in this work:

“Permar et al.(2021) found disagreement between PTR-ToF-MS, TOGA, and AWAS measurements of five species relevant to the OHR in BB smoke: isoprene, propene, furan, methyl furans, and monoterpenes. To limit the error from potentially interfering fragments while preserving temporal resolution in this work, PTR-ToF-MS isoprene and propene measurements were calibrated using co-measured TOGA and AWAS mixing ratios, resulting in near 1:1 agreement during the campaign. Similarly, TOGA furan and methyl furans are used for OHR calculations due to TOGA’s lower detection limits and lack of potential interfering isomers. As the PTR-ToF-MS measured furan and methyl furans approximately 1.5 and 15 × higher than TOGA, the OHR of these two species may represent a lower bound, while use of PTR-ToF-MS data would result in furans being an even larger OH sink. Finally, we note that PTR-ToF-MS measures the sum of monoterpenes at m/z 137.13, which is ~5 × higher than sum of camphene, α-pinene, β-pinene/myrcene, and tricyclene measured by TOGA, likely representing missing speciated isomers.”

Finally, the authors should better describe what leads to steady levels of formaldehyde and acetaldehyde in their plume aging discussion, as this continued production would be very important to capture in models.

We agree that the formaldehyde and acetaldehyde steady state is an interesting observation and would be an important feature for models to capture. Though, a full detailed analysis of the factors influencing their production and loss is beyond the scope of this work, we have added citations that their accurate representation by F0AM has been observed in previous studies. Additionally, we have added the following to the discussion: “For formaldehyde, a similar steady state was also observed in some FIREX-AQ sampled plumes, where the plume-to-plume variability was found to be dependent on OH concentrations, with OH-initialized VOC oxidation and photolysis being the main production and loss pathways.18,86 Conversely, acetaldehyde loss is primarily from reaction with OH radicals.86 Given acetaldehyde’s atmospheric lifetime against OH is ~1 day, Figure 5 suggest that it is likely from primary emissions.”


Specific comments:
Line 40 – You could consider citing this paper here (cited later on), as it that suggests that the OH bias in models must be over land - https://acp.copernicus.org/articles/20/7753/2020/.

Thank you for the suggestion, we have added the citation to line 40.

Line 53 – If you are going to bring up the topic of missing OHR, tell us whether there are any other measurements of OHR in fire plumes and whether there was significant missing reactivity.

To the best of our knowledge, Kumar et al. (2018) is the only study to report direct OHR measurements in biomass burning smoke, where they estimate ~40% missing OHR. Here, we bring up direct OHR measurements to define terms while leaving a detailed discussion of missing OHR for Section 3 where it can be discussed in more context.

Line 57 – Is that true, particularly for SOA? Oxidation by NO3 might matter as well.
https://www.pnas.org/doi/full/10.1073/pnas.2012218117

This is a good point. Our original statement was meant to be only in reference to OH initiated chemistry, we have softened this statement to account for the role of other oxidation pathways.

Intro - You could consider bringing up here the idea in the intro that wildfires bring VOC-rich air into VOC-limited cities and enhances ozone production from urban NOx as is discussed later in the paper – https://www.science.org/doi/full/10.1126/sciadv.abl3648.

Thank you for the suggestion. We added the idea in the introduction briefly.

Line 69 – This is because most of the emissions are CO2, so I am not sure this is an insightful statistic. You could give the fraction of non-CO2 emissions, but it would need to be compared to urban or forested settings to have meaning.

We agree that this statistic is a result of most of the emissions being CO2, CO, and CH4. It is included in the introduction to provide context for VOCs being the main OH sink in BB smoke as opposed to anthropogenic or free troposphere airmasses, for example, where CO, CH4, and NOx can make up a significant fraction of the OHR.

Line 73 – Furans only have a few hour lifetime, do they really contribute to aged smoke?

We have added “furan containing” to make this statement read more broadly. Though furan and many of substituted forms are short lived, some oxidation products such as maleic and succinic anhydride can have lifetimes of ~5 days (Coggon et al., 2019). For example, Liang et. al. (2022) showed that furanoids account for 8 % and 18 % of plume OHR in two smoke plumes having undergone 3 to 6+ hours of aging.

Line 95 – Coggon et al., 2019 did something very similar (https://acp.copernicus.org/articles/19/14875/2019/), possibly rephrase your text to describe how your study will be novel compared to that work. If the differentiator is that you consider aging here, possibly state their (and any other relevant findings) and then be clear about what you will add.

Thank you for this suggestion. We have rephrased the text to provide more context about how our work builds on what was done by Coggon et al., 2019. Specifically: “Here, we use a similar suit of instrumentation to build on the laboratory work done by Coggon et al. (2019) evaluating how the MCM represents OHR in wildfire emissions, while expanding the analysis to examine how the MCM captures OHR as wildfire smoke ages”

Line 103 – I would refrain from too many superlatives (i.e., ‘the first’, ‘the most’), as there have been many fire-related field campaigns. Just describe why WE-CAN is a unique dataset for your study.

We agree that there have been many fire-related field campaigns, though we do not believe it’s an overstatement that WE-CAN and FIREX-AQ represent a significant advancement in the amount of gas, aerosol, cloud, and meteorological measurements simultaneous made in wildfire smoke.

Table 1 – The text size in the top right-hand box of Table 1 seems larger than the rest.

The sizing has been fixed.

Can you tell us at some point whether the main species you call out (monoterpenes, furans etc.) had uncertainties of 50% or 15%? And how well they compared with WAS etc.?

This is an important piece of information that was originally missing from the manuscript. We have added uncertainties for all individual species to the supplement Table S1. We have also added a brief discussion of the measurements that were found to disagree between instruments as per the previous comment.

Line 157 – The choice of plume center vs. plume edges is even more reason to consider NO3 reactivity as optically-thick plumes have different oxidation characteristics in the center vs. edges https://acp.copernicus.org/articles/21/16293/2021/. It might be useful to understand whether it makes a difference to consider other metrics, such as plume-average concentrations, as models generally are unable to represent the plumes and must dilute the emissions immediately to the size of their grid box.

As discussed in our reply above, we agree that NO3 chemistry is important in optically dense plumes, especially for phenolics. Our choice to focus on the plume centers is twofold. First, we expect the plume center to be more representative of fresh emissions thereby lessening the extent of observed photochemical aging in plumes sampled 30+ minutes downwind of the source. Second, by focusing on the plume center our F0AM model inputs remain consistent across WE-CAN literature, allowing for better comparison between studies.

Line 161 – Why would you want to add in the regional background if you are trying to
understand the plume OHR? Wouldn’t you want to use only background-subtracted
concentrations?

Discussing the OHR profiles based on the absolute OHR (non-background corrected) provides a more apples-to-apples comparison between the different environments. This is because the urban plumes cannot be background corrected due to the way they were sampled, while there is no meaningful way to background correct free troposphere data. By using the absolute OHR then, we are discussing the OHR of the entire airmass, which is more descriptive of the overall OH sink in different environments. Additionally, because the regional background is very small compared to the OHR in the smoke plumes, using absolute OHR ultimately has little effect on the overall comparisons.

Line 165 – If you are comparing the plume concentration to the free tropospheric background, it seems to make the analysis more confusing not ‘easier’ if you do not subtract off the background. I do not understand this argument.

See response above.

Line 169 – Is there a reason you want to use physical age rather than photochemical age that would be more accurate in describing the state of the observed chemistry? For example the ratio of furan to maleic anhydride - https://doi.org/10.1021/acs.est.1c05684. Did the back trajectory analysis using windspeeds and fire location agree with this 3 day aging?

This is a very good point and relevant to the Reviewer’s comment about aging in the emission transects below. Here, we address the three analyses where the choice between using physical vs chemical age is relevant.

As the Reviewer points out, photochemical age may be more accurate in describing the extent of oxidation of a plume, particularly when the emission source is unknown or the smoke is well aged. In the context of line 169, we are discussing how the F0AM model results were compared with plume observations based on the physical age of each transect as calculated from fire location and measured windspeed. For this analysis, we use a physical age rather than a photochemical age due to it being the literature standard when comparing field observations to model output such as F0AM. This in part, reflects that physical ages are more intuitive to the reader than photochemical clocks, which are difficult to link back to physical parameters.

The > 3 days aging profile was estimated using photochemical tracers following Odell et al. (2020) such that we are describing the same aged smoke in the two papers. We did not perform back trajectory analysis on these smoke samples in either this work or in Odell et al. because much of the smoke that meets the filter criteria (Section 2.2) is difficult to attribute to any single fire. However, Odell et al. did find generally good agreement between ages estimated using photochemical tracers and those calculated using physical parameters when available. We have added the following sentence discussion the limitations of this estimate: “Though the calculated smoke age generally agrees well with physical age estimates, this method is sensitive to variability in fire emissions, dilution rates, and oxidant concentrations (O’Dell et al., 2020). Consequently, the absolute aging time is a best estimate and reflects smoke having undergone significantly more photochemical processing than the fresh emissions.”

In response to the comment below about the potential inclusion of aged smoke in our fresh emissions, we have chosen to include the 24 fires in our emissions profile based on a few factors. First, these are the same emission transects identified and used to calculate EFs in our previous work (Permar et al., 2021) and were not filtered further here to remain consistent between the two papers. Second, we used a physical age criterion to define these transects as fresh emissions to maximize sample numbers and improve statistics when calculating a campaign average, with the potential aging effect reflected in part by the deviation. Finally, similar to choosing a single physical age to define fresh/aged emissions, there is not a clearly defined cutoff for fresh/aged smoke based on the ratio of two species making the selection of which plumes to include somewhat arbitrary regardless of which aging metric is used.


Line 226 – Why choose GFAS? GFED4s I believe has more VOCs than GFAS, as does FINN. Could you at least comment on the VOCs available from other commonly used inventories?

We have updated the discussion in Section 3.4 to better explain why using different emissions inventories does not influence this analysis. As described in our response to Reviewer 1 above, the number of VOCs in the inventory does not matter for this analysis because we are only comparing the 21 species that are implemented for BB in GEOS-Chem. This was done to test how much OHR may be missing for BB as implemented in GEOS-Chem.

Line 274 – That is an enormous range in tOHR. Are the lower values really fresh fire plumes? Also, it seems like you need a reference to Figure S2 here. Line 275 – The reference 14 gives a range of 98 – 450, not 9-450. Figure S2 gives a range of 9 – 199, not 9 – 198.

Thank you for catching these typos, we have corrected the literature reference and our observed tOHR. The lower tOHR values are still from fire emissions as per our definition of emission transects. As the OHR is dependent on concentration, some of the lower values represent transects where the C130 may have been at the wrong altitude to capture the very center of the plume and therefore represent more dilute smoke. Similarly, some of the fires were smaller in size, such as the Red Feather prescribed burn (9 s-1) which was sampled ~20 minutes from the source. This is in part why we normalize the OHR to CO for much of the discussion.

Figure S3 – I don’t know if PAN is necessary here as it doesn’t show up.

We agree that PAN does not need to be included in either Figure 1 or Figure S2 as it makes up < 0.01 % of the total OHR. We have removed PAN from these figures as described in our response to a similar comment from Reviewer 1.

Figure S3 cont.: However, the ozone that appears relevant in the Carr Fire a and possibly the Bear Trap Fire b suggest that maybe these fires are too aged to be considered as fresh emissions? Clearly the range of HONO contribution indicates a large range in age. I would definitely use a photochemical clock like maleic anhydride to furan to determine if you really want to include all these fires.

Please see our response to why we use physical vs chemical age for why we chose to include these fires in our emission profile.

Line 291 – Here you give us info on missing OHR, possibly move it up near line 53, or remove the reference on line 53 and only discuss it here.

Thank you for the suggestion. Missing OHR is first introduced on line 53 to define the term in relation to the calculated OHR used in this work, while the more detailed discussion is left until here to provide better context. We believe that the current iteration, where missing OHR is defined on line 53 and then discussed in more detail in line 291, best communicates our point.

Line 299 – I am confused by this statement. Why would you speculate on 40% missing reactivity during WE-CAN according to Kumar et al. when you next state that NVOCs are unimportant?

We have edited this discussion to clarify that NVOC measurements made by PTR-ToF-MS can be highly uncertain and that we cannot entirely rule out the role of NVOCs in BB plumes. By including what missing 40 % of the OHR could mean for WE-CAN measurements we are instead providing a potential upper bound for our calculated tOHR.

Figure 1 – Make all your numbers have the same significant digits (probably two). Also, I do not see PAN show up on these charts, possibly it is not needed in the legend.

Figures 1 and S2 have been updated to have the correct number of significant digits. As mentioned above, PAN has been removed from the legend.

Line 332 – Are there any other factors such as seasonality or latitude etc. that would lead to expected differences in OHR between studies? It is not clear whether you are suggested free tropospheric OHR is likely always a similar value or not.

Tropospheric OHR is unlikely to be similar between studies because of the factors the reviewer mentions. We have clarified the discussion to reflect this.

Line 343 – Do you see any important transport of PAN into Boise?

Because PAN has a low OH reactivity, 2.2 x 10-4 s-1 on low/no smoke days and 3.8 x 10-4 s-1 on smoke impacted ones, we did not do any further assessment on how much was transported to Boise. However, looking back at the data PAN mixing ratios did increase from 350 ppt on low/no smoke days to 600 ppt on smoke impacted ones. We have added this change to the revision.

Line 357 – You gave a range for tOHR of 9-198 on line 273.

The 9-198 range is for all gas species and includes CO, CH4, NOx, etc. The 7-170 range on line 273 corresponds to OHR of just the VOC species.

Line 363 – Higher combustion efficiency generally results in lower VOC emissions as more is converted to CO2. What was measured in the lab studies that has a shorter lifetime than ~130 minutes and what are the implications for your results?

This is an important limitation to mention. We have added to following sentences to address this comment. “The tOHRvoc during WE-CAN then is likely a lower bound due to rapid oxidation of short-lived species such as monoterpenes, isoprene, and many furan containing compounds. Consequently, these species may make up a larger proportion of the tOHR in emissions sampled nearer to the source, while the contribution of photochemically produced OVOCs may be reduced.”

Line 365 –What are the implications of large disagreements for furans and monoterpenes between the WE-CAN instruments as discussed in Permar et al., 2021?

As discussed in the response to the comment above, we have sought to minimize this disagreement by using TOGA measured furan and methyl furans which does not have the same potential for interferences as the PTR-ToF-MS measurement. For monoterpenes, the disagreement discussed in Permar et al., (2021) is mostly attributed to the PTR measuring all potential monoterpene isomers, which more than 30 have been identified in BB smoke (Hatch et al., 2019), whereas TOGA only measured 4 during WE-CAN. We have added these details to the discussion in section 2.1.

Line 368 – Do you mean they are each equivalent to NOx, or their sum is?

We have added the word ‘each’ to clarify that we are talking about them individually.

Also, why choose top 10 when the model implementation discussed in Section 2.4 has 21? Showing the top 20 or 25 might make more sense, as you state that the species not shown are difficult for models to implement and that is a number that is currently implemented.

This is a good idea, however, we chose to limit Figure 2 to 10 VOCs in part because of spatial constraints, as adding 10 more species would make the figure quite large with species names difficult to read. Additionally, the magnitude of the axis scale would result in the boxes of many VOCs being illegible. We don’t think adding additional species would change the main point of this figure as regardless of how many species are implemented in GEOS-Chem, 5 of the most reactive are not currently included.

Also, how does Fig. 2 compare if lumped into GEOS-Chem species?

Figure 2 would be unaffected by lumping into GEOS-Chem species because those species shown in red are not incorporated into the standard model for BB emissions.

Figure 3 – Consider putting the urban and biogenic results referenced on line 395 on Fig. 3 to help make the point about the contrast with fires.

We agree that these OHR profiles would be great additions to Figure 3. Unfortunately, the results referenced on line 395 are from the literature, while we were unable to identify sampling periods with strong biogenic emissions during WE-CAN and urban emissions are already shown for Boise. The results on line 395 then, are included to provide context about how BB emissions are more diverse than many other environments.

Line 465 – What is the DO3/DCO in the fire plumes (e.g., Jaffe et al., 2012,
doi:10.1016/j.atmosenv.2011.11.0630) and in the descents into Boise in clean and fire-impacted data? Are the fires themselves providing some of this 13 ppb increase in ozone, or is it entirely driven by fire VOCs and urban NOx?

This is a very good question that we are not able to fully answer with our data alone. The average O3/CO ratio decreases during smoke impacted profiles (0.34 to 0.24 ppb O3 ppb CO-1), but we are unable to background correct the urban emissions because of how they were sampled. Similarly, we do not know the O3/CO ratio of the smoke that impacted Boise prior to its arrival. However, recent work using box modeling suggested the urban ozone production during smoky days in California is mostly due to local photochemistry. We added this discussion briefly in the revision.

Line 484 – This is a very oblique statement – can you at least tell us more specifically what other inventories you looked at?

We have edited this statement to include which other inventories we tested and better explain why the choice of emission inventory does not impact our analysis as discussed in the reviewer responses above

Line 516 – Is that true for GFED4?

Yes, this is true regardless of the emission inventory since it is the fraction of the WE-CAN calculated OHR for the 21 GEOS-Chem implemented species to the total OHR. As mentioned in the above comment, we have clarified the text to reflect this.

Figure 4 – Could you shade or mark on panel c) the fraction of furans, aromatics, butadienes, and monoterpenes stated in the text rather than showing it in a separate supplemental figure if possible. Or make a fourth panel?

We investigated doing this for the original submission but having two separate keys in the same figure is technically challenging and confusing to read. Additionally, we believe the current version of the figure better visualizes our key finding, that GEOS-Chem does not implement half of the field measured OHR for BB. We then leave the breakdown of the missing fraction to the discussion in the text. We have added a reference to the supplemental Figure S3 in the figure caption to further point readers to the additional information.

Line 523 – GEOS-Chem does simulate benzene, toluene, and xylene. Are you referring to other aromatics here?

Correct. benzene, toluene, and xylene are compared as implemented species. The remaining aromatics are compounds such as phenols and other substituted benzenes.

Line 555 – I do not see a purple dashed line on Figure 5.

We are unsure why the purple dashed line did now show up in the reviewers copy of the manuscript. It is visible in the originally submitted version and we will verify that it remains so upon re-submission.

Section 3.5 – Please provide a table or better description of how the F0AM model was run. Maybe just a supplemental table of the input file would be sufficient. How did you match up observed species to the mechanism? How did you treat photolysis over time? What is constrained/unconstrained, what is your dilution rate?

We have added more details about the F0AM model to section 2.5 and a supplemental table for initial values as discussed in our response above.

Could you possibly provide a map of the Taylor Creek fire+flight tracks to help us understand what you are modeling?

This is a great idea! We have added a flight track of the Taylor creek fire to Figure 5.

Line 562 – Please tell us the major drivers of production/loss resulting in steady levels
formaldehyde and acetaldehyde over time, as this would be very important for models to capture.

Please see our response to the major comment above.

Line 577 – Aren’t you using the PTRMS values to initialize the model? So isn’t this circular?

Although we use PTR-MS values to initialize the model, the MCM applies its own OH rate constants, which unlike those used in our direct calculations, are corrected for temperature and pressure by the model. Additionally, the weighted rate constants and speciation of the PTR ions used for our direct calculations and model initialization are based on literature derived isomeric fractional contributions. Because the field calculated OHR is expected to equal the model OHR for the same suit of species, this statement further validates that the assumptions used in our direct OHR calculations are valid.

Line 646 – You might consider listing the exceptions to this here such as xylenes, MACR, and MEK.

Thank you for the suggestion, we have added the exceptions to this discussion.





References:
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Decker, Z. C. J., Zarzana, K. J., Coggon, M., Min, K.-E., Pollack, I., Ryerson, T. B., et al. (2019). Nighttime Chemical Transformation in Biomass Burning Plumes: A Box Model Analysis Initialized with Aircraft Observations. Environmental Science & Technology, 53(5), 2529–2538. https://doi.org/10.1021/acs.est.8b05359
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22-Sep-2022

Dear Dr Permar:

Manuscript ID: EA-ART-06-2022-000063.R1
TITLE: Atmospheric OH reactivity in the western United States determined from comprehensive gas-phase measurements during WE-CAN

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************

Reviewer 1

My comments have been addressed.

Reviewer 2

The authors have improved the manuscript with their revisions. I have the following minor technical comments that should be addressed and then I will support this manuscript for publication.

Line 303 – The plume center mean tOHR is given as 75.3 s-1, but the value given in Figure 1 is 73.6 s-1.

Line 354 – OVOCs for the clean troposphere look more like ~0.14 s-1 in Fig. 1, not 0.22 s-1.

Figure 3 – It is surprising that there is isoprene/monoterpene/sesquiterpene reactivity in the free troposphere but not in aged smoke.

Line 574 – The authors might consider saying something about needing sufficient model resolution so as not to artificially mix fire smoke with anthropogenic emissions in a large grid box, particularly when considering highly reactive VOCs like monoterpenes.

Line 616 – I assume you mean from primary ‘precursor’ emissions, not primary acetaldehyde? Clarify in the text.

Here are the response to the Referee 2.

"The authors have improved the manuscript with their revisions.  I have the following minor technical comments that should be addressed and then I will support this manuscript for publication. "
"Line 303 – The plume center mean tOHR is given as 75.3 s-1, but the value given in Figure 1 is 73.6 s-1."
Thank you for catching this typo, the value shown in figure is correct and we have updated the text.

"Line 354 – OVOCs for the clean troposphere look more like ~0.14 s-1 in Fig. 1, not 0.22 s-1. "
The OHR of OVOCs is 0.15 s-1 in the free troposphere, but this line was meant to report the OHR of all VOCs, which is 0.22. We have updated the text to make this more clear.

"Figure 3 – It is surprising that there is isoprene/monoterpene/sesquiterpene reactivity in the free troposphere but not in aged smoke. "
It is likely that the reason terpenes can be seen in the free troposphere profile but not the aged smoke one is due to the magnitude of the total OHR for each. In both environments the terpen OHR is very low, 6e-3 s-1 in the free troposphere and 4e-4 s-1 in the aged smoke.

"Line 574 – The authors might consider saying something about needing sufficient model resolution so as not to artificially mix fire smoke with anthropogenic emissions in a large grid box, particularly when considering highly reactive VOCs like monoterpenes"
Thanks for the suggestion. Improving model resolution is a long-term target, and long standing issues for even for urban/forest environments, whenever/wherever we have heterogeneous emissions. It would depend on the progress in many areas including the software engineering. The context of this sentence and paragraph is that the CTMs miss a significant amount of reactive organic carbon from fires, and thus we recommend a priority list for the next stage of model development. We do not feel the need to emphasize model resolution here, as it had been addressed in many early studies. Nevertheless, we mentioned the proper model resolution in the revision.

"Line 616 – I assume you mean from primary ‘precursor’ emissions, not primary acetaldehyde?  Clarify in the text. "
That is meant to say the directly emitted acetaldehyde, since its lifetime is thought to be ~ 1 day, thus we’d not see much chemical loss within ~2 hours. We clarified it in the revision.

07-Oct-2022

Dear Dr Permar:

Manuscript ID: EA-ART-06-2022-000063.R2
TITLE: Atmospheric OH reactivity in the western United States determined from comprehensive gas-phase measurements during WE-CAN

Thank you for submitting your revised manuscript to Environmental Science: Atmospheres. I am pleased to accept your manuscript for publication in its current form. I have copied any final comments from the reviewer(s) below.

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