A study on the potential of higher education in reducing carbon intensity

Qin Yuan; Ruiqi Wang; Huanchen Tang; Xin Ma; Xinyue Zeng

doi:10.1371/journal.pone.0309546

Peer Review History

Original SubmissionApril 28, 2024
19 Jun 2024 Decision Letter - Bifeng Zhu, Editor PONE-D-24-17034A Study on the Potential of Higher Education in Reducing Carbon IntensityPLOS ONE Dear Dr. tang, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’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. ============================== Please supplement the theoretical framework and optimize the literature review. The rationality of methods (assumptions, calculation formulas, frameworks) needs to be further clarified. Clarify the conclusion of this paper, which should be specific and targeted. ============================== Please submit your revised manuscript by Aug 03 2024 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 plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols. We look forward to receiving your revised manuscript. Kind regards, Bifeng Zhu Academic Editor PLOS ONE Journal requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. In the online submission form you indicate that your data is not available for proprietary reasons and have provided a contact point for accessing this data. Please note that your current contact point is a co-author on this manuscript. According to our Data Policy, the contact point must not be an author on the manuscript and must be an institutional contact, ideally not an individual. Please revise your data statement to a non-author institutional point of contact, such as a data access or ethics committee, and send this to us via return email. Please also include contact information for the third party organization, and please include the full citation of where the data can be found. 3. We note that Figure 2 in your submission contain [map/satellite] images which may be copyrighted. All PLOS content is published under the Creative Commons Attribution License (CC BY 4.0), which means that the manuscript, images, and Supporting Information files will be freely available online, and any third party is permitted to access, download, copy, distribute, and use these materials in any way, even commercially, with proper attribution. For these reasons, we cannot publish previously copyrighted maps or satellite images created using proprietary data, such as Google software (Google Maps, Street View, and Earth). For more information, see our copyright guidelines: http://journals.plos.org/plosone/s/licenses-and-copyright. We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission: 1. You may seek permission from the original copyright holder of Figure 2 to publish the content specifically under the CC BY 4.0 license. We recommend that you contact the original copyright holder with the Content Permission Form (http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text: “I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.” Please upload the completed Content Permission Form or other proof of granted permissions as an ""Other"" file with your submission. In the figure caption of the copyrighted figure, please include the following text: “Reprinted from [ref] under a CC BY license, with permission from [name of publisher], original copyright [original copyright year].” 2. If you are unable to obtain permission from the original copyright holder to publish these figures under the CC BY 4.0 license or if the copyright holder’s requirements are incompatible with the CC BY 4.0 license, please either i) remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only. The following resources for replacing copyrighted map figures may be helpful: USGS National Map Viewer (public domain): http://viewer.nationalmap.gov/viewer/ The Gateway to Astronaut Photography of Earth (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/ Maps at the CIA (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.html NASA Earth Observatory (public domain): http://earthobservatory.nasa.gov/ Landsat: http://landsat.visibleearth.nasa.gov/ USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://eros.usgs.gov/# Natural Earth (public domain): http://www.naturalearthdata.com/ 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. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: Yes ******** 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? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: Using a panel dataset comprising 30 provinces in China, the author utilizes a fixed effects model to examine the influence of higher education on carbon intensity. Although the attractiveness of the subject matter, the paper suffers from serious problems. For the following reasons, we suggest this study to be appropriated with major revision. 1. The marginal contribution of this paper does not seem to be clear, please add the marginal contribution in the introduction section. 2. The theoretical aspect of this article is relatively insufficient. I believe that literature review cannot replace theoretical analysis. I suggest that the author add a section on theoretical analysis and improve the research hypothesis. 3. In the Empirical Analysis section, the author failed to control for time fixed effects and province fixed effects in benchmark regression and heterogeneity analysis, which is crucial for the accuracy of the estimation. Suggest the author to re estimate and control for time fixed effects and province fixed effects. 4. Heterogeneity analysis lacks coefficient difference testing and cannot directly compare sizes. Reviewer #2: This article explores the relationship between carbon emissions and higher education, offering a unique and innovative perspective. However, several areas require improvement and further clarification: 1. The author examined the impact of higher education on carbon emissions. However, environmental awareness education at the primary or secondary school levels also affects carbon emissions. How did the author account for the potential interference from primary and secondary education on carbon emissions? 2. In the Introduction section, the author explains the relationship between carbon emissions and higher education, but the discussion lacks depth. It is recommended that the author further elaborate on the relationship between higher education and carbon emissions by integrating existing research. Additionally, the author should consider reducing some of the common knowledge content in the Introduction. 3. The author has obtained some quantitative conclusions, but these are not reflected in the abstract. It is recommended that the author include some quantitative conclusions in the abstract. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? 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.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0309546.r001
Revision 1
20 Jul 2024 Author Response Dear Editor and Reviewers: We sincerely thank you and the reviewers for the very helpful comments and constructive suggestions that have led to significant improvements of our paper. We have carefully addressed your comments point-by-point in the revised manuscript. Specific responses are placed in an additional file for editors and reviewers. The main changes and revisions include 1) We reworked the introduction section to further add the relationship between carbon emissions and higher education and to increase the marginal contribution of the article.; 2) We added 2.3 Theoretical analysis and research hypothesis to refine the research hypotheses; 3) In the empirical research section, we re-estimated and controlled for time fixed effects and province fixed effects, and reworked the heterogeneity analysis; 4) We reworked the abstract section to add quantitative results. We hope that the changes and responses to comments in the revised manuscript are sufficient to make our manuscript suitable for publication in PLOS ONE. Response to reviewer 1's comments Using a panel dataset comprising 30 provinces in China, the author utilizes a fixed effects model to examine the influence of higher education on carbon intensity. Although the attractiveness of the subject matter, the paper suffers from serious problems. For the following reasons, we suggest this study to be appropriated with major revision. Thank you very much for the reviewer's recognition of the topic and the following suggestions, we have carefully revised the article according to your suggestions, and the main changes are as follows: 1) We reworked the introduction section to further add the relationship between carbon emissions and higher education and to increase the marginal contribution of the article; 2) We added Theoretical analysis and research hypothesis to refine the research hypotheses; 3) In the empirical research section, we re-estimated and controlled for time fixed effects and province fixed effects, and reworked the heterogeneity analysis; 4) We reworked the abstract section to add quantitative results. 1. The marginal contribution of this paper does not seem to be clear, please add the marginal contribution in the introduction section. Response 1: Many thanks to the reviewers for their suggestions, and we have added the marginal contribution of this paper in the Introduction section（Lines 77-88）. This study analyzes the relationship between higher education and carbon intensity across thirty provincial administrative regions in China using a fixed-effects model. To strengthen the robustness of our findings, we substituted the core explanatory variables, further validating our conclusions. The analysis then categorizes China into eastern and central-western regions to explore regional disparities in the impact of higher education on carbon intensity. Additionally, we developed a mediation effect model that elucidates the roles of technological innovation incentives, environmental awareness promotion, and industrial structure enhancement in mediating this relationship. Based on these insights, we offer targeted policy recommendations. In comparison to existing studies, this paper makes three primary contributions: First, it proposes a theoretical framework from the perspective of higher education, thereby broadening the environmental governance discourse. Second, it addresses both the spatial variability in higher education and its differential impacts on carbon intensity, considering both educational inputs and outputs. Third, it identifies critical mechanisms such as technological innovation, environmental awareness, and industrial upgrading that link higher education and carbon intensity. 2. The theoretical aspect of this article is relatively insufficient. I believe that literature review cannot replace theoretical analysis. I suggest that the author add a section on theoretical analysis and improve the research hypothesis. Response 2: The reviewers' suggestions are greatly appreciated. We have re-added Theoretical analysis and research hypothesis to more systematically organize the theory and improve the research hypothesis of this paper（Lines 172-207）. Theoretical analysis and research hypothesis From a behavioral economics standpoint, highly educated individuals typically exhibit a heightened sense of social responsibility. They are more attentive to environmental sustainability and actively oppose lifestyles and consumption habits characterized by high energy use. Such individuals are predisposed to adopting pro-environmental behaviors and demonstrating a robust environmental consciousness. In both professional and personal contexts, they prefer to efficiently utilize idle resources, opt for low-carbon transportation solutions, and use environmentally friendly products. For example, as consumers, educated individuals tend to favor purchasing electric vehicles to mitigate carbon emissions43. Furthermore, educated entrepreneurs and managers are more likely to uphold corporate social responsibilities, advocate for sustainable production methods, and minimize the ecological impact of their business operations. According to human capital theory, education and training represent crucial investments in human capital. Higher education not only augments workers' professional knowledge and practical skills but also fosters their capacity for innovation and research. This comprehensive enhancement significantly improves their level of knowledge, professional abilities, and overall competencies, thereby increasing their potential future earnings and job prospects. The educational advancement of the workforce contributes to the accumulation and diversification of human capital, which, in turn, drives the growth of high-tech industries and the evolution of industrial structures. Consequently, this shift leads to the displacement of traditional high-pollution industries by more sustainable high-tech and green sectors, effectively reducing carbon intensity. Theoretical economics suggests that higher education not only raises an individual’s knowledge level but also generates knowledge spillover effects. This educational process not only benefits the learners themselves but also exerts a positive influence on the wider society. By engaging in both educational and research activities, universities can attract technology-driven enterprises to establish collaborative platforms such as joint laboratories, technology transfer centers, and innovation incubators. These platforms not only enable joint research projects and technological advancements but also facilitate the specialized training of innovative talent. They promote local technological innovation, catalyze the development of emerging clean technologies, improve resource efficiency in production, and ultimately contribute to a reduction in carbon intensity. Based on the analysis above, this paper illustrates the discussed mechanisms in Figure 1 and proposes the following hypotheses: Hypothesis 1: Higher education can significantly suppress carbon intensity. Hypothesis 2: Higher education reduces carbon intensity through the mechanism of promoting environmental awareness. Hypothesis 3: Higher education reduces carbon intensity through the mechanism of upgrading industrial structures. Hypothesis 4: Higher education reduces carbon intensity through the mechanism of incentivizing technological innovation. Fig 1. Mechanistic analysis of higher education and carbon intensity. 3. In the Empirical Analysis section, the author failed to control for time fixed effects and province fixed effects in benchmark regression and heterogeneity analysis, which is crucial for the accuracy of the estimation. Suggest the author to re estimate and control for time fixed effects and province fixed effects. Response 3: For the empirical analysis section, we re-estimated and controlled for time-fixed effects and province-fixed effects in accordance with your recommendations（Lines 345-372）. Estimated Results of Fixed Effects Model In this study, the Hausman test on panel data was conducted using STATA 17. The results indicate a p-value below 0.01, rejecting the null hypothesis of random effects. Subsequently, annual dummy variables were introduced to assess the presence of individual time effects. The results also reveal a p-value below 0.01, strongly rejecting the null hypothesis of "no time effects," confirming the existence of time effects in the model. As a result, a two-way fixed effects model is chosen to explore the impact of higher education on carbon intensity. For comparative purposes, this model incorporates the mixed effects model and random effects model. Table 4 presents the regression results for (1) mixed effects model (OLS), (2) random effects model (RE), and (3) two-way fixed effects model (FE). In general, upon observing the regression results in Table 4, the coefficient of determination R2 for the mixed-effects model in Model 1 is 0.659, for the random-effects model in Model (2) is 0.621, and for the two-way fixed-effects model in Model (3) is 0.921. This indicates that the two-way fixed effects model exhibits the best overall fit. Notably, from the regression results in the column (3) of Table 5, the core explanatory variable, higher education, exhibits a negative coefficient. Higher education demonstrates a significant negative correlation with carbon intensity. On average, for every 1% increase in the logarithmically transformed per capita higher education investment, carbon intensity in a given provincial-level administrative region decreases by 0.219%. This result is statistically significant at the 1% level and hypothesis 1 is tested. The empirical findings suggest that higher education investment significantly suppresses regional carbon intensity. China can enhance production efficiency in various sectors and resource utilization by increasing higher education investment, thus reducing carbon emissions and promoting ecological environment improvement. With respect to the CV, the regression coefficients for the economic development (lnpgdp) and population density (density) are negative and both statistically significant at the 1% level. On average, carbon intensity decreases with higher economic development and population density. Regression coefficients for urbanization and energy consumption are positive, with urbanization being statistically significant at the 1% level and energy consumption at the 5% level. Carbon intensity increases with higher levels of urbanization and energy consumption. Other factors such as transportation, trade openness, social consumption, and infrastructure development also exert certain impacts on carbon intensity, but these impacts are not statistically significant. Tab 4. Regression Results. Varible OLS RE FE (1) (2) (3) lnedu -0.427** -0.183* -0.219* (0.190) (0.103) (0.085) lnpgdp -0.207 -0.562* -1.213* (0.274) (0.200) (0.164) Density -0.460 -0.526* -0.872* (0.17) (0.147) (0.335) Urban -0.239 0.253 0.634* (0.157) (0.276) (0.181) lncar -0.318 -0.093 -1.161 (0.252) (0.329) (0.207) Open -0.087 -0.183 -0.081 (0.071) (0.074) (0.087) Consump 0.152*** 0.069* 0.049 (0.053) (0.040) (0.036) Energy 0.253 0.184 0.260 (0.110) (0.083) (0.120) lnmile -0.144 -0.048 0.222 (0.137) (0.261) (0.146) Constant 0.006 -0.009 -2.107* (0.08) (0.095) (0.355) Time FE NO NO YES Province FE NO NO YES N 600 600 600 R2 0.659 0.621 0.921 Note: Standard errors are shown in parentheses; , * and *** indicate the significance at the 10%, 5% and 1% levels, respectively. 4. Heterogeneity analysis lacks coefficient difference testing and cannot directly compare sizes. Response 4: Based on your suggestions, we have reworked the heterogeneity analysis. Heterogeneity Analysis The economic landscape in our nation exhibits a stratified progression from the eastern coastal areas to the western inland regions. Variations in natural and cultural settings may influence the efficacy of higher education. This study categorizes the entire sample into eastern and central-western regions based on the classification method employed by the National Bureau of Statistics. Regression analysis, detailed in Table 7, demonstrates that higher education significantly reduces carbon intensity across both regions, with a more pronounced effect in the central-western region—a finding corroborated by the inter-group coefficient difference test. This disparity may stem from the central-western region's less favorable geographical and economic conditions, which render its energy structure and technological innovation more responsive to advancements in higher education, thereby facilitating a reduction in carbon intensity. Tab 7. Heterogeneity Analysis. Varible Eastern region Central and Western region (1) (2) lnedu -0.318* -0.827* (0.094) (0.129) Control YES YES Time FE YES YES Province FE YES YES N 220 380 R2 0.724 0.891 Test for difference in coefficients between groups for lnedu 0.047* Note: Standard errors are in parentheses; *, , and * represent significance levels of 1%, 5%, and 10%, respectively; empirical p-value results for the test of coefficient of variation between groups were obtained by bootstrap sampling 1000 times. Response to reviewer 2's comments This article explores the relationship between carbon emissions and higher education, offering a unique and innovative perspective. However, several areas require improvement and further clarification: Thank you very much for the reviewer's recognition of the topic and the following suggestions, we have carefully revised the article according to your suggestions, and the main changes are as follows: 1) We reworked the introduction section to further add the relationship between carbon emissions and higher education and to increase the marginal contribution of the article.; 2) We added Theoretical analysis and research hypothesis to refine the research hypotheses; 3) In the empirical research section, we re-estimated and controlled for time fixed effects and province fixed effects, and reworked the heterogeneity analysis; 4) We reworked the abstract section to add quantitative results. 1. The author examined the impact of higher education on carbon emissions. However, environmental awareness education at the primary or secondary school levels also affects carbon emissions. How did the author account for the potential interference from primary and secondary education on carbon emissions? Response 1: 为了排除小学或中学阶段的环保意识教育也会影响碳强度，本文分别从高等教育投入与高等教育产出视角选择自变量，其中高等教育投入角度本文选取高等教育方面的人均公共预算支出作为各地区高等教育水平的指标;高等教育产出角度本文选取人均教育年限和高等教育的人口比例作为高等教育的代理变量，考虑到目前中国已普及义务教育，因此人均教育年限和高等教育人口比例可以很好的反应中国高等教育产出情况。In order to rule out the influence of environmental awareness education at the elementary and secondary school levels on carbon intensity, this paper selects independent variables from the perspectives of higher education inputs and outputs. For the perspective of higher education inputs, this paper chooses the per capita public budget expenditure in higher education as an indicator of the level of higher education in various regions. From the perspective of higher education outputs, this paper selects the average years of education per capita and the proportion of the population with higher education as proxy variables for higher education. Considering that compulsory education has been universalized in China, the average years of education per capita and the proportion of the population with higher education can effectively reflect the outputs of higher education in China. This approach allows for a more effective demonstration of the variations in investment in higher education by local governments. The specific measurement methodology adopted in this study is: In this analysis, 'Edu' denotes the level of local higher education, as reflected by the per capita public budget expenditure on higher education. 'Budget' signifies the public fiscal allocation for higher education, while 'Number' indicates the the number of students enrolled in local general colleges and universities.. Data pertaining to the public fiscal allocation for higher education and university enrollments are obtained from th Attachments Attachment Submitted filename: Response to reviewer 2s comments.pdf https://doi.org/10.1371/journal.pone.0309546.r002
14 Aug 2024 Decision Letter - Bifeng Zhu, Editor A Study on the Potential of Higher Education in Reducing Carbon Intensity PONE-D-24-17034R1 Dear Dr. tang, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. 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 onepress@plos.org. Kind regards, Bifeng Zhu Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The author has fully addressed my concerns and hopes that this research can contribute to the relevant field. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No ******** https://doi.org/10.1371/journal.pone.0309546.r003
Formally Accepted
19 Aug 2024 Acceptance Letter - Bifeng Zhu, Editor PONE-D-24-17034R1 PLOS ONE Dear Dr. Tang, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset If revisions are needed, the production department will contact you directly to resolve them. If no revisions are needed, you will receive an email when the publication date has been set. At this time, we do not offer pre-publication proofs to authors during production of the accepted work. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few weeks to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Bifeng Zhu Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0309546.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .