https://orcid.org/0009-0005-3680-9690
Peer Review History
| Original SubmissionApril 20, 2025 |
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PCLM-D-25-00118 The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018 PLOS Climate Dear Dr. Nguyen, Thank you for submitting your manuscript to PLOS Climate. After careful consideration, we feel that it has merit but does not fully meet PLOS Climate’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Reviews agree that the manuscript addresses an important topic, but requires revision. Please address reviewer comments on the methods, including statistical analysis performed, the disparity metric (absolute vs. relative), and the use of the averaging window and time periods. While further explanation and justification may suffice, additional analysis is recommended. Table 1 is also noted as a source of difficulty (or possible redundancy). Finally, the clarity of the writing could be improved, particularly to consistently define and apply technical terms. Please submit your revised manuscript by Jul 09 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at climate@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pclm/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
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(http://www.naturalearthdata.com/about/terms-of-use/)-->?> Additional Editor Comments (if provided): [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Does this manuscript meet PLOS Climate’s publication criteria?> Reviewer #1: Partly Reviewer #2: Partly ********** 2. Has the statistical analysis been performed appropriately and rigorously?-->?> Reviewer #1: Yes Reviewer #2: Yes ********** 3. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: Yes ********** 4. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: Yes ********** Reviewer #1: The study “The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018” explores how wildfire smoke has changed PM2.5 pollution in California from 2006 to 2018. The authors break down the changes in concentrations for communities of different socioeconomic and racial composition to quantify how wildfires have contributed to disparities over time. The study mostly achieves this goal by characterizing and comparing exposures for each category. I believe this study will be a valuable contribution to the literature because wildfire smoke is expected to increase with time; as the wildfire contribution can be difficult to parse, its contribution to existing disparities remains poorly quantified. Major comments: I think that, at times, the analysis techniques are slightly too simple to make a strong argument about temporal trends. For example, in various parts of the paper, the authors compare individual years (2006 vs 2018) or groups of years (2006-2008 vs 2016-2018) without much justification for why these periods were chosen. Although I do not think that the existing analysis is wrong, given the large role of interannual variability, I do think that the case would be stronger if trends were calculated over the whole time periods (and compared against each other) rather than only focusing on differences between parts of the study period. Relatedly, a couple conclusions that are drawn in the discussion would be strengthened through slightly more analysis (see minor comments; 375, 387). I think the text could use some editing throughout the manuscript. Though I can mostly understand what is being said, there are quite a few sentences that could be clearer and more precise. This is most relevant is the use of certain terms like “correlation,” and especially “disparity,” which are used inconsistently in different contexts. This sometimes led me to be confused about the argument. I have made note of several but not all of the places that I thought could use more clarity in the minor comments. I thought that that story sometimes got lost a bit in descriptive statistics and using clearer language could help more directly state the message. The authors did address the broader role of wildfires on disparities a bit in the discussion, but I think it could use more. I was left with a few questions, e.g.: If disparities are decreasing does it matter that it is being caused by wildfires? In most years wildfire smoke increases disparities slightly (Fig 3C) - I think this is somewhat contrary to the main conclusions of the paper; what does it imply about the role of geography in exposure? Are you able to speculate about what the implications of this will be in the future? Given that “absolute difference” is used as a metric, I’m wondering why relative difference was not used at all. This is a common metric in other papers. Of course the authors cannot explore every metric, but given that the chosen metric is referred to as “absolute” and disparities are often discussed in relative terms, I think a bit of text in the Methods or Discussion about why these quantities were chosen over others is warranted. On a similar note, I think the story could be tied a bit more directly to other studies that have quantified disparities and their trends in the US and CA - there are many and they are currently pretty sparsely cited. Minor comments: 49: the use of “avoidable” is vague here 50: PM2.5 is not just an indicator of air pollution, it’s a major component 69-69: I think it’s worth clarifying that these reductions did not just happen in the 21st century 70: Given the current political climate I think it makes sense to explicitly note the year and/or administration for the EO 81: Why is education mentioned here? If just listing factors I would move that to wherever SES is introduced/described 85: “(Total mass)” is unnecessary 87: This makes it sound like wildfire is policy driven - a little unclear what the connection is 102-103: Exposure to disparities is a confusing phrase - please clarify 118: It’s unclear to me from this sentence whether you calculated something or used a previously published dataset 126: I think it would help to say minus the estimated non-wildfire PM (if I understood correctly) 146: It would be helpful to have more description of the Spearman correlation. Throughout the paper the word “correlation” is used in different ways like “Spearman correlation”, “Spearman coefficient”, “rank-rank correlation”, or just “correlation”; given how widely used the word “correlation” is across disciplines and contexts, I think it would be clearer to describe it clearly in the methods and then pick one terminology to use consistently throughout the whole manuscript. 183: I personally think it would be more meaningful to include population-weighting Fig 1: I think it would be helpful to add a a map of just mean concentration for reference 248: I had to read this sentence several times. The “while” makes it sound contradictory, but I think the two halves of the sentence are stating the same point? Table 1: I think this table could probably be moved to the supplement since it is hard to digest quickly and the information is mostly contained in Figure 3. Furthermore I don’t really understand why the authors are now comparing two three-year periods. I think the time series is more informative. 279: It is stated here that the disparities narrow, but in other parts of the paper (Figure 2) the opposite argument is made. I believe the difference comes from different definitions in disparity, but I think that distinction should be made more clearly. 296-298: I don’t think I really agree with this characterization. The years seem a bit arbitrarily chosen. My interpretation would have been increasing 2010-2014 and decreasing thereafter. 307: I’m not worried about formal significant digits, but I think these percentages are implying considerably higher precision than is actually available. I would recommend removing one or two decimal places, at least for the text. 308-312: I think this summary could be stronger. It was just stated that values in 3C are mostly positive (“consistently positive over time” on line 299) and yet here only one year is pointed out as being positive. So I’m somewhat unsure what the authors think the takeaway should be. 324: I realize I am quibbling about semantics a bit, but I found “individuals” distracting since no individuals are studied, it’s just communities/populations/people. And despite saying it would be referred to as individuals, the text immediately switches to the word residents. 348: This is probably a matter of personal preference/style, but I would find this paragraph more interesting if it was a little less focused on reporting the numbers in the figure and a bit more focused on patterns and changes from wildfire. E.g. I think it would be fine to say that A and B look mostly the same and focus instead on where they differ by describing the wildfire plot, rather than repeating very similar numbers for A and B. 369: Citation required for first discussion sentence 372: I don’t understand the phrase “structural drivers of environmental justice driven sources of pollution” 375: “partially attributable” would be stronger if you could assign a number to it, which I think would be pretty straightforward within the context of what has already been done. 387: “much less pronounced” is again a little vague. I think I see the point being made, but to me 4A and 4B look quite similar. I think this could be strengthened by, for example, calculating the trend for both panels and showing that the trend decreases by X% when excluding wildfire smoke. 393/396: I think these lines say that policies reduce absolute differences but don’t reduce disparities. I’m confused about how these terms are being used because the absolute differences in Figure 4 are referred to as disparities. 412: “reverse” seems like a strong word - maybe diminish? Reviewer #2: Review of The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018 In this manuscript, Nguyen et al. examine trends in exposure disparities to PM2.5 in California and the contribution of wildfire smoke to these trends. They find that total PM2.5 exposure and exposure disparities have decreased over time, due to both decreases in non-wildfire PM2.5 and increases in wildfire PM2.5. While I agree with the authors that disentangling the role of increasing wildfire smoke in ongoing PM2.5 exposure disparities is important, I have some concerns about the methods used and conclusions made and believe that the overall clarity and conciseness of the manuscript needs to be improved prior to publication. See below for specific comments and recommendations. Major Comments: 1. In general, the methods seem to be quite simple for the proposed analyses, and there is not sufficient justification for some of the methodological decisions made. For example, a large part of the analyses relied on 3-year averages for 2 time periods (2006-2008 and 2016-2018). While the methods state that 3-year averages were used to be a “better representation of long-term exposure,” why weren’t 4-, 5-, or 6- year averages considered to represent long-term exposure? Additionally, if the goal was to examine high fire activity years, why were averages over multi-year periods used (which can dilute estimates of PM2.5 exposure during high fire years), rather than focusing on exposure year-to-year, which would enable an understanding of differences in exposure disparities in years with high vs. low fire activity? The 3-year average approach ignores a lot of valuable data between 2009-2015, and at present there is not sufficient justification for the selected averaging window and time periods. If the authors want to keep this approach, at minimum I would recommend adding additional justification for the selection of methods and including results for all 3-year periods between 2006-2018. Additionally, I think there may be value in applying more sophisticated approaches to understanding changes and disparities in population exposure to total, wildfire, and non-wildfire PM2.5 over time – for example, could you estimate the magnitude or significance of the trends in exposure and exposure disparities over time, or test for significant differences between types of PM2.5 exposure or population groups? Beyond looking at averages of PM2.5, could you measure how much of wildfire vs. non-wildfire PM2.5 contributed to exposure disparities each year? Is there value in looking at the exposure disparities by composite indicators of vulnerability (e.g., social vulnerability index), which are readily available and would allow for a more nuanced understanding of exposure disparities by intersecting risk factors? Overall, additional justification for the selected methods needs to be provided, and the authors should consider expanding their analyses to include additional years and/or approaches to better explore the contribution of wildfire smoke to PM2.5 exposure disparities over time. 2. I am not convinced that some of the key takeaways are supported by the results presented in the manuscript. For example, the discussion states that: “Our finding indicates that substantial efforts are still needed to address inequalities in air pollution exposure related to locally actionable sources of PM2.5,” and that “in the absence of wildfire PM2.5 contributions to the trends in total PM2.5 disparities, improvements towards exposure equity were much less pronounced.” However, the results largely indicate that across the board, PM2.5 exposure disparities have decreased, due both to decreases in non-wildfire PM2.5 and increases in wildfire PM2.5. While some disparities still exist, as shown in Figures 3 and 4, the trends in Figure 3A and 3B and Figure 4A and 4B for total and non-wildfire PM2.5 look largely the same, and one could argue that an absolute difference of 0.5 ug/m3 does not indicate that a significant disparity in exposure is present. The conclusions and key takeaways need to better match the results presented. 3. Table 1 should be re-organized to enhance readability – the table should allow the reader to compare changes in sociodemographic indicators between the two time periods (i.e., has the populations exposed to the most/least total, wildfire, and non-wildfire PM2.5 changed over time?). Right now, if a reader wants to see how the % Hispanic in the most and least exposed areas has changed between 2006-2008 and 2016-2018, it is quite difficult to do. 4. Overall, the clarity of the writing could be improved. All the necessary content is included, but some of phrasing of sentences and inclusion or exclusion of certain terms make the text difficult to follow in places. See minor comments below for some examples. To ensure the key points come across and to enhance readability, I would recommend improving the conciseness and clarity of the writing. Minor Comments: 1. Line 27: The phrasing “exposing communities… more differently” is a bit strange when discussing differences in patterns of exposure between wildfire PM2.5 and typical ambient PM2.5. Consider rewording. 2. Lines 35-36: The statement “Yet, this reduction has been mostly driven by wildfire PM2.5.” needs to be elaborated on – was the reduction in rank-order disparity in total PM2.5 due increases in exposure to wildfire PM2.5 across all RE and SES groups? 3. Line 42: “Our results suggest that policies addressing structurally-driven sources of PM2.5 remain insufficient.” – is this what the results suggest? The results included in abstract demonstrate that there has been a reduction in disparities in exposure to PM2.5, in part due to reductions in non-wildfire PM2.5 (which are the structurally-driven sources). 4. Line 51: “inhalable mixture less than or equal to 2.5...” should be changed to “inhalable mixture of particles less than or equal to 2.5…” 5. Line 52: The 2015 GBD estimates are used here, but there are more recent GBD estimates available – I would recommend updating this to reference the more recent results. 6. Lines 59-62: This sentence is unclear in its current form, and the information included here appears to be redundant with the information provided in the previous sentence. I would recommend clarifying the point trying to be made here. 7. Line 92: “different spatial patterns than other PM2.5” should be changed to “different spatial patterns than other sources of PM2.5” 8. Line 93: I would recommend adding more of a “why” here – why are white, Hispanic, American Indian, and more affluent Americans more exposed to wildfire PM2.5? Is it because of where these populations live relative to where wildfire smoke tends to occur? 9. Line 94: “Wildfire smoke might also pose more risk in disadvantaged groups due to limited abilities to evacuate and higher prevalence of existing conditions” – a key reason wildfire smoke poses a greater risk to disadvantaged groups is differences in the ability to mitigate exposure, not just evacuate – i.e., can they afford an air cleaner? Do they live in an older, leakier home? Do they have access to a clean air shelter? I would recommend adding some of these points here. 10. Line 97-98: “…given the complexity of wildfire causes” – this is a good point to make, but I would recommend clearly stating that a key difference between reducing exposure to wildfire smoke PM2.5 vs. reducing exposure to other sources of PM2.5 is that wildfire smoke is much more difficult to regulate with policies like the CAA (e.g., we can’t simply reduce the emissions of wildfire smoke) 11. Line 123-125: This sentence reads as if non-wildfire PM2.5 was estimated by using PM2.5 data on days with wildfire smoke. I would assume that non-wildfire PM2.5 would be estimated using PM2.5 data on days without wildfire smoke (i.e., days where there was not a smoke plume present). If this is the case, I would recommend clarifying this sentence. 12. Line 207: Were census tracts with populations <1,000 or <1,500 removed? It says 1,000 here, but 1,500 on Line 181. 13. Line 369-374: This sentence could be re-written to better communicate the key point being made here 14. Figure S2 – the maps in A-C look identical to the maps in D-F, which is not expected given the lower fire activity in 2006. I would check if these maps are correct. ********** what does this mean? ). If published, this will include your full peer review and any attached files. Do you want your identity to be public for this peer review? 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| Revision 1 |
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PCLM-D-25-00118R1 The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018 PLOS Climate Dear Dr. Nguyen, Thank you for submitting your manuscript to PLOS Climate. After careful consideration, we feel that it has merit but does not fully meet PLOS Climate’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. The revised manuscript is significantly improved. Reviewers note additional minor corrections to address. In particular, the acknowledgement of 2018 as an unusual year and the resulting impact on claims in the manuscript seem to be common among reviewers and important context for readers. Please submit your revised manuscript by Oct 29 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at climate@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pclm/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript:
Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. We look forward to receiving your revised manuscript. Kind regards, Rebecca K. Saari Academic Editor PLOS Climate Journal Requirements: If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice. Additional Editor Comments (if provided): [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author Reviewer #1: (No Response) Reviewer #2: (No Response) ********** Reviewer #1: Partly Reviewer #2: Yes ********** 3. Has the statistical analysis been performed appropriately and rigorously?-->?> Reviewer #1: (No Response) Reviewer #2: Yes ********** 4. Have the authors made all data underlying the findings in their manuscript fully available (please refer to the Data Availability Statement at the start of the manuscript PDF file)??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: Yes ********** 5. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: Yes ********** Reviewer #1: The authors have made significant improvements to the manuscript. The text is often clearer and many of my main comments were addressed. However, at times, the text still contains statements that are not well supported by the data, usually stemming from the role of the outlier in 2018, and describing comparisons between individual years as trends. The information contained in the data is interesting and relevant, but I urge the authors to be more precise in their language to avoid unsupported text. The most notable instances of this issue are described below, followed by minor text comments. Substantive text changes: 43: Although I understand the sentiment, I don’t think the last sentence of the abstract is well justified by the paper. In fact, the previous sentences say that climate change has equalized exposure, so why does climate change necessitate more efforts to reduce inequities? I think the masking argument in the previous sentence is much stronger. 255: I don’t think the statements in this paragraph are well justified. 2018 is clearly an outlier so it’s not fair to say that wildfire PM exposure increased by 850% from 2006 to 2018. Though the statement is not technically incorrect, the way this is written makes it sound like there is a trend despite not having any analysis of trends. This is sort of acknowledged in the next paragraph but I think the text around these statements needs to be significantly edited or removed to avoid misinterpretation. I think the variability in the wildfire data is too high to draw any conclusions by comparing just two years. The supplemental figures comparing multiple years are helpful, but the text in this section should better reflect the differences in those figures. 387: This conclusion needs to be more specific or include several qualifiers. The time series in 4c has a lot of variability. That’s fine and interesting, but saying that disparities widened from 2006 to 2018 does not seem justified by the existing analysis. 422: This paper does not show anything about policy action - it’s fine to reference citation 38 and say what other papers have shown, but this statement is not backed by the research in this paper. 497: Again, I’m not convinced it’s fair to say wildfire PM concentrations increased from the evidence presented. Minor text comments: 49: “distributed unevenly by countries and regions” is a bit unclear 349: I suggest removing “towards zero” since it is unnecessary and it sounds to me like it implies it’s asymptoting towards a number close to zero. Same with the parenthetical “(but were not completely eliminated)” on 353. They are maybe half in some cases, which is a notable difference, but saying they’re not completely eliminated makes it sound like they are mostly gone. 402: I think there’s a word missing somewhere (maybe “2008 and 2018”?) because there are two percentages. 420: “were not as effective in completely eliminating those disparities” is a confusing phrase because it implies the policies were better at reducing total air pollution than they were at reducing disparities, which was not shown here. I would recommend changing this to something like “our results show that despite these policies, disparities persist, as demonstrated…” 424: Aren’t these differences by definition institutional/systemic racism? 451: I recommend switching the last two sentences of this paragraph for readability (and changing “simultaneously” to “therefore”) 461: “temporally SES groups” missing “by” Reviewer #2: I thank the authors for thoughtful revision of their manuscript, which has addressed the majority of my concerns. I have a few additional comments for consideration prior to publication: 1. Some of the wording in the methods is still a bit unclear and could be revised for increased clarity. A few examples below. I would recommend ensuring that the wording throughout the manuscript clearly communicates the approaches used. “We assigned the 5-year estimates of 2006-2010 to years 2006 to 2010, the 5-year estimates of 2011-2015 to years 2011 to 2015, and the 5-year estimates of 2015-2019 to years 2016 to 2018, to account for the prominent change in census tract boundaries in 2020” – since all of the data is for before 2020, how does this approach account for changes in the boundaries in 2020? “Census tract-level non-wildfire PM2.5 concentrations in wildfire smoke days identified through satellite smoke plume data were then estimated through imputation with chained random forest algorithm and total PM2.5 during non-wildfire days.” – “in” should be changed to “on,” and it would much clearer if you first introduce how wildfire smoke days were identified and then explained how those wildfire smoke days were used to estimate non-wildfire PM2.5. “To provide information on how PM2.5 exposure in each census tract changes relative to other census tracts in California, we used rank-rank comparisons to evaluate changes in PM2.5 exposure over time across census tracts in California” – this sentence is redundant, and the part following “rank-rank” comparisons could be removed or incorporated into the first part of the sentence. 2. The comparison between 2006 and 2018 is a focus of the results, but it is not clearly acknowledged that 2018 was an extremely high fire year in California (third worst on record). The results, especially for the temporal changes in wildfire PM2.5 (e.g., lines 250-259), should provide better context that this comparison is between a lower fire year and a very high fire year, and provide the context that any spatial trends (e.g., those noted in line 257) are a reflection of the fires that burnt in 2018, and are not necessarily indicative of broader spatial and temporal trends in wildfire PM2.5. This context could also be more clearly provided throughout the discussion when discussing the results for 2018. 3. “Wildfire PM2.5 contributed to 107.6%,…” – how can the contribution be over 100%? If we’re talking about contributions to the total exposure disparity, the sum of all contributions should be 100% and wildfire PM2.5 accounts for some portion of that 100%. The terminology and methodology used to calculate these numbers should be clarified. ********** what does this mean? ). If published, this will include your full peer review and any attached files. Do you want your identity to be public for this peer review? If you choose “no”, your identity will remain anonymous but your review may still be made public. For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: No Reviewer #2: No ********** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] |
| Revision 2 |
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The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018 PCLM-D-25-00118R2 Dear Nguyen, We are pleased to inform you that your manuscript 'The diverging role of increasing wildfire smoke to ambient PM2.5 exposure disparity in California, 2006 to 2018' has been provisionally accepted for publication in PLOS Climate. Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow-up email from a member of our team. Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated. IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they'll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact climate@plos.org. Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Climate. Best regards, Rebecca K. Saari Academic Editor PLOS Climate *********************************************************** Additional Editor Comments (if provided): Reviewer Comments (if any, and for reference): |
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