Research on the Distribution Dynamics and Convergence of Renewable Energy in China

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I think that the term “renewable energy” (no matter how popular) is logically wrong. According to basic physics laws, energy cannot renew by itself. So why the perpetum mobile machine does not exist. Consider to use terms like “green”, “clean”, “low-carbon”, “low-emission” instead. But remember that solar and wind energy can be also called “unstable energy sources”, and remember that carbon dioxide is only 0.04% of the whole atmosphere.

Generally the structure of the paper is good. The choice of methods is always somehow a subjective matter. I like your choice. It’s good that you present basic formulas, so readers not good in statistical measures can see some details.

Some detail remarks:

• Line 89 – change “thesis” into something different (“study”, “paper”, “research”)
• Line 316 – the title of Table 2 is too general. “Descriptive statistics” of what? What is you statistical unit (one province in one year – spatio-temporal object?). Why sample size is 480
• Figures 1, 2, 5 – time series shown on these graphs are rather smooth. It would be interesting to fit trend function and show some forecasts
• Line 396 and 397 and information below tables 8 & 9 – According to widely accepted Kolmogorov’s definition probability has no unit. Significance level is a accepted probability of rejecting null hypothesis which is actually true. So 0.01 and not 1%; 0.05 not 5%, and 0.10 not 10%.

 

Author Response

We sincerely thank you for your insight into the accuracy of the term. Your comment raises an important semantic discussion that deserves clarification. In this paper, “renewable energy” refers to energy sources (such as water, solar, wind) that can be continuously replenished by natural processes, and whose renewability is reflected in the sustainability of the energy source, rather than the regeneration of the energy itself. "Renewable energy" is the official term of the United Nations, the International Energy Agency and other authorities, and has been widely accepted by the scientific community and the public. Substituting "green energy" may obscure its core characteristics (such as nuclear power being low-carbon but non-renewable). The manuscript needs major revision before it can be published in the journal. The comments of this work are as follows:

Comment 1. Line 89 - change “thesis” into something different (“study”, “paper”, “research”).

Responds: We sincerely appreciate the reviewer’s valuable feedback.

We have realized that changing the word “thesis” into “study” can better reflect the research nature of the paper. And we have made the change in the revised manuscript (line 92). In the future research, we will also bear this in mind and maintain a rigorous attitude towards academics.

 

Comment 2. Line 316 - the title of Table 2 is too general. “Descriptive statistics” of what?  What is you statistical unit (one province in one year - spatio - temporal object?). Why sample size is 480.

Responds: We apologize for the oversight in the paper, for not clearly stating descriptive statistics about what it was about, and for failing to clearly explain why there were 480 sample sizes in the article.

We took your advice and added a detailed note after table 2 (line 335-336) to make readers have a better understanding. And the revised table in the revised manuscript is as follows:

Variables	Sample size	Mean value	Standard deviation	Minimum	Maximum
REGPC	480	1,157	1,869	0.814	14,300
EM	480	0.226	0.236	0.000242	0.919
IC	480	0.466	0.736	0.000814	6.264
GDP	480	46,429	29,368	6,103	187,526
UR	480	0.564	0.137	0.275	0.896
ER	480	0.00321	0.00295	0.000044	0.0245
CCPC	480	3.612	3.595	0.0597	21.93

Note: The statistical unit is province-year observations, consisting of 30 provinces over 16 years (30×16=480).

 

Comment 3. Figures 1, 2, 5 - time series shown on these graphs are rather smooth. It would be interesting to fit trend function and show some forecasts.

Responds: We appreciate your suggestion on trend analysis. Your suggestion gives us a new inspiration, and we will keep it in mind to find out the fitting function in the future research on the trend of change. And we summarized some of the changing trends in the article (line 362-364).

 

Comment 4. Line 396 and 397 and information below tables 8 & 9 - According to widely accepted Kolmogorov’s definition probability has no unit. Significance level is a accepted probability of rejecting null hypothesis which is actually true. So 0.01 and not 1%; 0.05 not 5%, and 0.10 not 10%.

Responds: Thank you sincerely for your insightful feedback and for bringing this issue to our attention. We deeply appreciate the time and effort you dedicated to reviewing our manuscript. In response to your comment, we have thoroughly revised the relevant sections of the article to address the concern.

Specifically, line 493, line 502, line 509, line 521, and line 531were revised. And in the future research, we will keep this point in mind in the future. Thank you again for your patience and help.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

This study explores the distribution dynamics and convergence of renewable energy in China, a crucial topic for addressing regional disparities in energy development. The research employs the Dagum Gini coefficient, nuclear density estimation, and convergence models to quantify spatial and temporal changes. However, the study does not clearly articulate its novelty or how it differs from existing research. The introduction lacks a well-defined research gap, and recent Q1 publications (2022–2025) should be incorporated to strengthen the contextual foundation. Additionally, the manuscript’s readability suffers from awkward phrasing and excessive passive voice, which should be refined for clarity and coherence.

The methodology lacks transparency, particularly in data selection, validation, and sensitivity analysis. Essential details, such as which databases were used for the literature review, are missing and should be clearly specified. Sections 2.1 and 2.2 primarily list findings without critical discussion—authors should contrast perspectives and provide their own insights. Additionally, multiple instances of "Error! Reference source not found." appear throughout the manuscript and must be corrected. The tables also require better alignment and formatting to enhance clarity and consistency.

The results section presents findings but lacks comparative discussion, making it difficult to assess their significance within the broader literature. More emphasis should be placed on practical implications for policymakers and energy sector stakeholders. Additionally, Table 9 appears oversaturated, and scientific notation could improve readability. The conclusion and policy recommendations should be separated into distinct sections to avoid redundancy. To improve logical flow, informal academic styling such as "Remark:" should be replaced with natural transitions.

The figures require substantial improvements to enhance readability and professionalism. Figures 1 and 2 suffer from small text labels and poor color contrast, making them difficult to interpret. The left-axis orientation should be corrected for accuracy, and a contextual map should be added to provide a more precise geographic reference. Figure 4 lacks professional formatting, with the red columns being nearly imperceptible. Additionally, the figure on page 13 lacks a title and classification system, making it difficult to interpret—recreating it using professional software such as Origin, R, or Python would improve clarity.

Overall, the manuscript presents potential data but requires significant revisions to improve clarity, methodological transparency, and data visualization. Strengthening these areas, refining the discussion of findings, and enhancing English readability will significantly improve the paper’s impact. 

Comments on the Quality of English Language

A professional language edit is highly recommended before resubmission to ensure fluency and coherence.

Author Response

Thank you for giving us detailed and specific suggestions on this article, which gives us the opportunity to further improve and revise it. Thank you for your time and effort, the comments and responds are as follows:

Comment 1. This study explores the distribution dynamics and convergence of renewable energy in China, a crucial topic for addressing regional disparities in energy development. The research employs the Dagum Gini coefficient, nuclear density estimation, and convergence models to quantify spatial and temporal changes. However, the study does not clearly articulate its novelty or how it differs from existing research. The introduction lacks a well-defined research gap, and recent Q1 publications (2022–2025) should be incorporated to strengthen the contextual foundation. Additionally, the manuscript’s read ability suffers from awkward phrasing and excessive passive voice, which should be refined for clarity and coherence.

Responds: Thank you for your careful suggestion.

We add in line 231-line 234 to clarify the research gap. Previous studies focused on single renewable energy types, whereas this work integrates wind, hydro, and solar energy while employing advanced methods (Dagum Gini coefficient, spatial β convergence) to analyze regional disparities comprehensively.

Moreover, we added 2023–2024 Q1 studies (Bashir M F, Shahbaz M, Malik M N, et al. Energy transition, natural resource consumption and environmental degradation: the role of geopolitical risk in sustainable development[J]. Resources Policy, 2023, 85: 103985.) on the relationship between energy transition and environmental sustainability.

We have changed some passive voice to active voice in the revised manuscript (Line 215, we did the change from “It is found” to “They found”. Line 347, we did the change from “it can be seen” to “we can find”. Line 491, we did the change from “it can be seen” to “we can see”). We believe that making changes based on your suggestions will greatly improve the readability of our paper.

 

Comment 2. The methodology lacks transparency, particularly in data selection, validation, and sensitivity analysis. Essential details, such as which databases were used for the literature review, are missing and should be clearly specified. Sections 2.1 and 2.2 primarily list findings without critical discussion—authors should contrast perspectives and provide their own insights. Additionally, multiple instances of "Error! Reference source not found." appear throughout the manuscript and must be corrected. The tables also require better alignment and formatting to enhance clarity and consistency.

Responds: Thank you for pointing this out. Maybe we didn't explain it very clearly in the article.

We provided detailed data sources on lines 306-311 in the revised manuscript, which are also commonly used for energy research. In Table 1, the meaning, symbol and definition of each variable are explained in detail. Thank you again. We have adjusted the layout and format of Table 1, hoping to enhance the readability of the article.

In lines 231-234, we explain our views on the differences of previous studies on renewable energy, pointing out that the number of renewable energy selected in their studies is relatively limited, which cannot represent renewable energy well, and explain the innovation of our research, which is more representative of renewable energy by combining the analysis of wind energy, water energy and solar energy.

About the "Error! Reference source not found." and misalignment of data in the form. These problems did not occur when we submitted and checked the manuscript, which may be due to changes in the later revision. We will fix these problems to increase the clarity and consistency of the articles and tables. Thank you again for your reminding and suggestion.

 

Comment 3. The results section presents findings but lacks comparative discussion, making it difficult to assess their significance within the broader literature. More emphasis should be placed on practical implications for policymakers and energy sector stakeholders. Additionally, Table 9 appears oversaturated, and scientific notation could improve readability. The conclusion and policy recommendations should be separated into distinct sections to avoid redundancy. To improve logical flow, informal academic styling such as "Remark:" should be replaced with natural transitions.

Responds: Thank you for your advice on this issue, which we have made in our policy recommendations for policymakers and the energy sector. We would like to explain to you that our paper focuses more on the descriptive study of regional differences, distribution dynamics and convergence of the development of renewable energy, rather than on the change of a certain variable or different mechanisms affecting the development of renewable energy, so it cannot make detailed comparative discussion.

As you suggested, we have divided the Conclusions and policy recommendations into two parts to avoid redundancy. And we believe that this change will make the structure of our articles clearer and more rational.

We used remark once in the article (line 228 in the revised manuscript). Thank you for your suggestion. We will try our best to avoid using remark in future scientific research and focus on the natural transition of the article.

 

Comment 4. The figures require substantial improvements to enhance readability and professionalism. Figures 1 and 2 suffer from small text labels and poor color contrast, making them difficult to interpret. The left-axis orientation should be corrected for accuracy, and a contextual map should be added to provide a more precise geographic reference. Figure 4 lacks professional formatting, with the red columns being nearly imperceptible. Additionally, the figure on page 13 lacks a title and classification system, making it difficult to interpret—recreating it using professional software such as Origin, R, or Python would improve clarity.

Responds: We sincerely appreciate the reviewer’s valuable feedback.

We have corrected the layout of the table to align the numbers up and down, enhancing the clarity and standardization of the table. We also realized that confidence intervals should be written in terms of 0.01, 0.05, 0.1, rather than 1%, 5%, 10%. Specifically, line 493, line 502, line 509, line 521, and line 531 were revised. And in the future research, we will keep this point in mind in the future.

In order to facilitate reading, we adjusted the left axis label text direction, and unified the curve color of all curves to make the chart more professional. The Global Moran index change chart's ordinates have been adjusted to make the red columns more noticeable, but the change is still subtle due to the very small p-values in later years.

Figures on page 13 were made by using Matlab, and the layout of these five figures was a very troublesome problem. At the beginning, we had to arrange them side by side to make the layout clean, so we unified the figure on page 13 in a table, so that we could not insert cross-references, and finally lacked the title and classification system. We change as follows, arrange these 5 pictures in order, write the title and clarify the classification system.

 

Comment 5. Overall, the manuscript presents potential data but requires significant revisions to improve clarity, methodological transparency, and data visualization. Strengthening these areas, refining the discussion of findings, and enhancing English readability will significantly improve the paper’s impact.

Responds: In the process of revising the paper, we systematically optimized the presentation of the table.

For the nine core data tables (Table 1-9) in the text, we focus on the following aspects: First, the font size (Times New Roman, word 10) and cell alignment (center alignment) of the table are standardized; Secondly, the column spacing is optimized to ensure that the data hierarchy is clear. At the same time, redesign the layout of table headings and notes, so that table numbers, headings and footnotes form a clear three-level information structure. After adjustment, the visual presentation effect of all tables has been significantly improved compared with the first draft, and the professionalism and readability of data display have been effectively enhanced.

As for the problem of English expression you pointed out, on the premise of preserving the necessary passive voice to maintain academic objectivity, we have optimized the sentence pattern transformation of the whole manuscript, and strive to improve the language fluency while maintaining academic writing.

Thank you in particular for your valuable suggestions during the reviewing process. Your keen observation of the details of the data and the precise guidance of English expressions (such as highlighting redundant passive sentence patterns) have helped us to establish a more professional academic writing practice. We have established a revision memorandum to focus on the typical problems you have pointed out as improvements for future essay writing. Thank you again for your professional review and careful guidance.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

1. Carefully check if the numbering statements are consistentin the abstract.
2. The English expression in the article is inaccurate. Please seek assistance from an English professional to make corrections, such as line 383, 384, 395…
3. The literature review is not sufficient in the introduction, please enrich the relevant literature on thedevelopment of renewable energy.
4. The formula (1-5) symbols have not been explained in detail
5. The data in Table and Figure are insufficiently explained, please explain the results indicated by the data.
6. Line 269, what is the f(x) ?

Comments for author File: Comments.pdf

Author Response

Thank you for your understanding and recognition of our articles, and thank you for your suggestions on our articles

Comment 1.Carefully check if the numbering statements are consistent in the abstract.

Responses 1: Thank you for pointing out in detail the normative issue of cohesive words in the abstract. We do use different forms of ordinal adverbs ("first" and "secondly" alternately) in the abstract. This inconsistency of numbering forms violates the principle of coherence in academic writing.

In order to solve this problem, we decide to use uniform adverb numbering, and adjust the adverb form of "first, second, third and fourthly" in the original draft to "firstly, secondly, fourthly". Ensure the standardization and conciseness of academic expression. The revised abstract is as follows:

Abstract: It is important to study the difference, distribution dynamics and convergence of China's renewable energy development level to stimulate its potential. Based on China's provincial panel data from 2006 to 2021, this paper analyzes the regional characteristics of China's renewable energy development using Dagum Gini coefficient, nuclear density estimation, σ convergence and spatial β convergence, and draws the following conclusions: Firstly, renewable energy in the country and the four major regions have achieved stable growth; Secondly, the intra-group differences in China and the four major regions are gradually decreasing, and the contribution rate of inter-group differences to the overall differences is gradually increasing, which is the main source of the overall differences. Thirdly, the national renewable energy development has a positive spatial correlation; Fourthly, there are σ convergence and spatial β convergence in the whole country and the four major regions, the σ convergence coefficient gradually decreases, and the β convergence regression coefficient is significantly negative. Therefore, this paper proposes the following recommendations: formulate government policies according to local conditions, strengthen technical exchanges and cooperation among regions, encourage investment in renewable energy development, thus we can promote the realization of the "dual carbon" goal more efficiently.

 

Comment 2. The English expression in the article is inaccurate. Please seek assistance from an English professional to make corrections, such as line 383, 384, 395…

Responses 2: Thanks for your careful suggestion.

We have modified line 394-396. "The net difference between groups increased from 50.77% in 2006 to 74.24% in 2021, an increase of 46.22% "is changed to" The net difference between groups increased from 50.77% in 2006 to 74.24% in 2021, and there was an increase of 46.22%" (line 394-396 in the revised manuscript), which effectively improved the accuracy of expression. In addition, we have changed some passive voice to active voice in manuscript (Line 215, we did the change from “It is found” to “They found”. Line 347, we did the change from “it can be seen” to “we can find”. Line 491, we did the change from “it can be seen” to “we can see”). We believe that making changes based on your suggestions will greatly improve the readability of our paper.

 

Comment 3. The literature review is not sufficient in the introduction, please enrich the relevant literature on the development of renewable energy.

Responses 3: Thank you very much for pointing out our shortcomings in literature review, we have a wealth of relevant literature on renewable energy development.

We have complementary energy transition and renewable energy development impacts on environmental sustainability, the literature review supplement (line 190-194 in the revised manuscript) is as follows:

 Bashir M F et al. (2023) found energy transition and banking developments ensure environmental sustainability.

Ma B et al. (2023) found energy transition and renewable energy improve environmental sustainability, while non-renewable energy consumption exacerbates environmental challenges.

 

Comment 4. The formula (1-5) symbols have not been explained in detail

Responses 4: Thank you for pointing out that the explanation of our formula is not detailed.

We have supplementary explanations on the Dagum Gini coefficient formula in line 274-277, the Moran index calculation formula in line 282-285, and the Gaussian kernel density estimation formula for one-dimensional data in line 292-294. There are supplementary formulas for calculating σ convergence in line 300-302 and for calculating β convergence in line 309-314. Thanks again for your advice.

 

Comment 5. The data in Table and Figure are insufficiently explained, please explain the results indicated by the data.

Responses 5: Thank you for your detailed advice on our chart data.

We realized that confidence intervals should be written in terms of 0.01, 0.05, 0.1, rather than 1%, 5%, 10%. Specifically, line 515, line 524, line 531, line 543, line 553 and line 588 were revised. And in the future research, we will keep this point in mind in the future. Since our graph and table are a common set of data, we also have to strengthen the interpretation of the data, strengthen the description of the curve changing trend (line 421-422), and explain the results shown by the data as much as possible (line 349-352, line 361-363, line 383-395).

 

Comment 6. Line 269, what is the f(x)?

Responses 6: Thank you very much for pointing out this problem.

It is a careless mistake we made when writing manuscript, in this case should be f(y) kernel density function, not f(x). Line 288-289 states that f(y) is a calculation formula for estimating the nuclear density of renewable energy development, and the specific meaning of each character is specified in line 292-294. We are sorry that we did not check this problem at the beginning, thank you again.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This paper wrote in line with the journal. However, I have some tips on this paper for the authors.

1. Tittle, Abstract and Keywords

Renewable Energy should be added in Keywords.

Some words and sentences are incorrectly:

--Line 8-9 “It is important to study the difference, distribution and convergence of China's renewable energy development level to stimulate the development potential of China's renewable energy.” “China's renewable energy” was used two times, this expression is not very good.

--Line 13 “in the country” should be “in China”.

 

2. Introduction

This section should not be listed as 1.1, 1.2 and 1.3. The authors should explain the phenomenon that reflects the problem with data, and put forward the object of study accurately.

 

3. Literature review

The authors merely list the references without their own thoughts. It would be beneficial to attempt to identify common conclusions drawn by certain references.

 

4. The formatting of equations and tables should be improved. Additionally, there are multiple instances of incorrect table extraction in the text (for example, the error in line 315), which is the basic errors that should not occur.

 

5. Table 4 in the text can directly reflect the average values, and no-color/more academic graph is recommended in the article.

 

6. Table 9 just lists the results of the tests and does not address the reasons for these effects.

Comments on the Quality of English Language

 The English could be improved to more clearly express the research.

Author Response

Thank you for your constructive feedback on our manuscript. We have carefully revised the paper based on your suggestions. Below is a point-by-point response to the comments.

Comment 1. Tittle, Abstract and Keywords.

Renewable Energy should be added in Keywords.

Responses 1: We sincerely appreciate the reviewer’s valuable feedback.

We have added “Renewable Energy” to the Keywords section (Line 23 in the revised manuscript).

Keywords: The difference; Distribution dynamics; Convergence; Renewable energy

 

Comment 2. Line 8-9 “It is important to study the difference, distribution and convergence of China's renewable energy development level to stimulate the development potential of China's renewable energy.” “China's renewable energy” was used two times, this expression is not very good.

Responses 2: Thank you for your time and attention.

The sentence,“It is important to study the difference, distribution and convergence of China's renewable energy development level to stimulate the development potential of China's renewable energy.” has been revised to“It is important to study the differences, distribution, and convergence of China’s renewable energy development level to stimulate its potential.”(Line 8-9 in the revised manuscript)

 

Comment 3. Line 13 “in the country” should be “in China”.

Responses 3: Thank you for your careful advice. That’s so kind of you.

We agree with what you have put forward and have listened to your suggestions. We have revised all the problems in the article (line 13, line 64, line 206, line 447, line 543 and line 570 in the revised manuscript).

 

Comment 4. Introduction

This section should not be listed as 1.1, 1.2 and 1.3. The authors should explain the phenomenon that reflects the problem with data, and put forward the object of study accurately.

Responses 4: Thank you for your thoughtful advice.

We made changes to the Introduction, such as integrating all 1.1, 1.2, 1.3, and changing "structure of thesis" to "structure of study", which was also suggested by another reviewer. Thank you again for your valuable advice.

Moreover, we have added data to explain the fact that China currently leads the world in the total amount of renewable energy, but the per capita amount is low. “By 2023, China's total installed capacity of renewable energy exceeded 1,450 gigawatts (GW), accounting for about 35% of the world's total installed capacity. China's renewable energy generation reached 2.7 trillion kilowatt-hours (TWh), accounting for 34 percent of the country's total power generation and 28 percent of global renewable energy generation. Per capita installed renewable energy capacity is about 1.03 kilowatts (kW). Renewable energy generation per capita is about 1,914 kilowatt-hours (kWh)”(line 49-54 in the revised manuscript).

 

Comment 5. Literature review

The authors merely list the references without their own thoughts. It would be beneficial to attempt to identify common conclusions drawn by certain references.

Responses 5: Thank you for your careful advice.

We agree with what you have advised and have add a “remark” at the end of the literature review. In the remark below, we describe the limitations of existing studies, specifically, most scholars only select a certain type of renewable energy (such as wind energy, water energy, solar energy), but we integrate three types of renewable energy (wind energy, water energy, solar energy), so our research on regional differences, distribution dynamics and convergence of renewable energy is representative and convincing. The remark is detailed as follows:

Remark: There are many factors affecting the development of renewable energy, including positive factors and negative factors. By referring to the research results of scholars and teachers, I can expand my understanding of the development of renewable energy. Many scholars and teachers have used wonderful and rich methods to discuss the development of renewable energy in China in detail and in depth, which has great reference for my paper. However, most of the articles have analyzed the regional differences and distribution dynamics of wind energy, solar energy, water energy and other energy sources separately. This paper will comprehensively consider wind energy, water energy and solar energy. Dagum Gini coefficient was used for intra-group and inter-group differences, and the causes of intra-region and inter-region differences were analyzed. Kernel density was used to study the dynamic distribution characteristics of national and regional development levels, and the changes of renewable energy development levels in China and the four major regions over time were analyzed. Conduct σ convergence analysis, observe the change of σ convergence coefficient, and test the change of the degree of deviation from the average level of renewable energy development in each region over time; The spatial β convergence analysis was carried out, and the absolute β convergence and conditional β convergence methods were used to test whether the region with low level of renewable energy development could catch up with the high level region and narrow the gap between regions.

 

Comment 6. The formatting of equations and tables should be improved. Additionally, there are multiple instances of incorrect table extraction in the text (for example, the error in line 315), which is the basic errors that should not occur.

Responses 6: Thank you for pointing out this problem.

We also found that there was a problem with the form format in manuscript, which was not found when we submitted manuscript and reviewed view submission. Now we have revised the alignment of all forms in manuscript, such as table 9. Thus, the tables will be more organized. We also complete the units of the variables.

Variables	Symbol	Definitions
Per capita renewable energy generation(kWh)	REGPC	Renewable energy generation/population
Economic development level (Chinese yuan)	GDP	GDP per capita
Urbanization rate (%)	UR	Urban population / permanent population
Environmental regulation (%)	ER	Completed investment in industrial pollution control / added value of secondary industry
Energy structure (%)	EM	Renewable energy generation / Total power generation
Renewable energy infrastructure (GW)	IC	Per capita installed renewable energy capacity
Fossil energy endowments(t)	CCPC	Per capita coal consumption

 

 

Comment 7. Table 4 in the text can directly reflect the average values, and no-color/more academic graph is recommended in the article.

Responses 7: Thank you very much for your suggestion.

We have accepted your suggestion to change some of the trend charts to colorless charts. But our idea of juxtaposition is that the data in the table is the source of the graph, and the graph can clearly and intuitively show the trend over the study period, so please allow us to use the graph together.

 

Comment 8. Table 9 just lists the results of the tests and does not address the reasons for these effects.

Responses 8: Thank you for pointing out the problem we missed.

We have actively taken your suggestions and made changes. The lack of specific description and analysis of the data in table 9 is our negligence. We have added a discussion of the mechanisms behind the spatial β-convergence results (Line 530-531 and line 541-544 in the revised manuscript).

 

Comment 9. Comments on the Quality of English Language

 The English could be improved to more clearly express the research.

Responses 9: Thank you for your advice on the grammar of our language.

We reduced the use of passive voice in the article and improve the readability of the article. We have changed some passive voice to active voice in manuscript (line 215, we did the change from “It is found” to “They found”. Line 347, we did the change from “it can be seen” to “we can find”. Line 491, we did the change from “it can be seen” to “we can see”). Moreover, we find the numbering statements are not consistent in the abstract. In order to solve this problem, we decide to use uniform adverb numbering, and adjust the adverb form of "first, second, third and fourthly" in the original draft to "firstly, secondly, fourthly". Ensure the standardization and conciseness of academic expression. The revised abstract is as follows:

Abstract: It is important to study the difference, distribution dynamics and convergence of China's renewable energy development level to stimulate its potential. Based on China's provincial panel data from 2006 to 2021, this paper analyzes the regional characteristics of China's renewable energy development using Dagum Gini coefficient, nuclear density estimation, σ convergence and spatial β convergence, and draws the following conclusions: Firstly, renewable energy in the country and the four major regions have achieved stable growth; Secondly, the intra-group differences in China and the four major regions are gradually decreasing, and the contribution rate of inter-group differences to the overall differences is gradually increasing, which is the main source of the overall differences. Thirdly, the national renewable energy development has a positive spatial correlation; Fourthly, there are σ convergence and spatial β convergence in the whole country and the four major regions, the σ convergence coefficient gradually decreases, and the β convergence regression coefficient is significantly negative. Therefore, this paper proposes the following recommendations: formulate government policies according to local conditions, strengthen technical exchanges and cooperation among regions, encourage investment in renewable energy development, thus we can promote the realization of the "dual carbon" goal more efficiently.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for your careful attention to the initial comments and the revisions made so far. Meaningful improvements have been implemented, especially in separating conclusions from policy recommendations, correcting formatting, and incorporating additional literature. These changes help the manuscript move in the right direction.

That said, several core concerns remain unresolved or only partially addressed. The claimed novelty of examining wind, solar, and hydro together using Gini and convergence modelling still lacks a clear distinction from existing literature. This contribution should be more explicitly and convincingly communicated throughout the abstract, introduction, and discussion. Without this, the manuscript risks blending into prior work. Besides some references MUST be added in the introduction section!

The methodology section continues to raise concerns. Descriptions remain largely procedural, offering limited explanations of why certain models were chosen, what assumptions were tested, or whether alternative frameworks were considered. A lack of robustness checks or sensitivity analysis also undermines the strength of the findings.

Moreover, while the structure of the results section has improved, interpretation remains shallow. Trends are presented without adequate critical comparison to prior studies or implications for regional energy strategies. The figures, though better formatted, still fall short in quality and clarity, so professional reprocessing is recommended. FIGURE 1! Make more professional and add labels properly to support your idea

Comments on the Quality of English Language

A professional language edit would help elevate the manuscript to publication standards. Overall, the study has potential, but more substantial revisions are needed to ensure it meets both scientific and editorial expectations.

Author Response

We sincerely thank you for pointing out the problems existing in our article, such as insufficient display of research innovation points, insufficient reference materials, the need to improve the professionalism of the figures, and the relatively shallow policy suggestions. We believe that your suggestions have been of great help to us, and we also firmly believe that with your assistance, our article can be more professional, clear and understandable. We have also made specific responses and improvements to the suggestions that you gave. The comments of this work are as follows:

 

Comment 1. That said, several core concerns remain unresolved or only partially addressed. The claimed novelty of examining wind, solar, and hydro together using Gini and convergence modelling still lacks a clear distinction from existing literature. This contribution should be more explicitly and convincingly communicated throughout the abstract, introduction, and discussion. Without this, the manuscript risks blending into prior work. Besides some references MUST be added in the introduction section!

Responses 1: We are very grateful for your suggestion. We made changes to the Introduction and Literature review. In the article, we have supplemented the innovative aspects of conducting a comprehensive study on the differences and convergent properties of the three renewable energy sources by using the Dagum Gini coefficient, σ convergence and β convergence models.

In the introduction, we have included references on the wide application of renewable energy input (line 48-51, we added “With the rapid development of renewable energy, we have applied sustainable energy in various fields, such as the civil engineering and construction industry (Liu,2024), automotive transportation(Li et al., 2021; Li et al., 2022) and the manufacturing industry sector(Taibi, 2012).”); We described the structure of the article in more detail (line 102-103, we added “Finally, we have given some policy suggestions for the development of renewable energy in section 6.” ). We have also made corresponding modifications to the Literature review. In the "Remark" section, we have detailed the literature that conducted research using a certain renewable energy source to distinguish the innovativeness of this article's research integrating the three renewable energy sources (line 250-252, “However, most of the articles have analyzed the regional differences and distribution dynamics of wind energy, solar energy, water energy and other energy sources separately(Wu et al., 2012; Chen et al., 2012; Yan et al., 2015; Li et al., 2022).”). We also described the marginal contribution of this article (line 252-259, “Firstly, we comprehensively considered the three major renewable energy sources (wind energy, hydropower and solar energy), which is more representative compared with analyzing a single renewable energy source separately. Secondly, in the article, we divide the provinces of China into four major regions according to the classification method of the National Bureau of Statistics of China, which is more professional. Thirdly, our research will take into account the spatial correlation of renewable energy development among various regions.”). We also added the references using the Dagum Gini coefficient and the convergence model, which are also the reference sources for the model in our article (line 260-262, “In this paper, we used Dagum Gini coefficient (Ma et al.,2022;Zhou et al.,2022, Chen et al.,2021) for intra-group and inter-group differences, and the causes of intra-region and inter-region differences were analyzed”; line 265-271, “Moreover, we conducted σ convergence analysis (Chen et al., 2021), observed the change of σ convergence coefficient, and tested the change of the degree of deviation from the average level of renewable energy development in each region over time; The spatial β convergence analysis was carried out, and the absolute β convergence and conditional β convergence methods were used to test whether the region with low level of renewable energy development could catch up with the high level region and narrow the gap between regions.”).

 

Comment 2. The methodology section continues to raise concerns. Descriptions remain largely procedural, offering limited explanations of why certain models were chosen, what assumptions were tested, or whether alternative frameworks were considered. A lack of robustness checks or sensitivity analysis also undermines the strength of the findings.

Responses 2: Thank you very much for your suggestions. We attach great importance to your suggestions.

In the paper, we added the reasons for choosing the Dagum Gini coefficient instead of the traditional Gini coefficient, and elaborated in more detail the differences between absolute β convergence and conditional β convergence. We also conducted Wald tests and LR tests on the conditional β convergence that requires control variables and passed the tests.

Furthermore, the research on the differences, spatial correlations and distribution dynamics of renewable energy development in China in our article does not involve control variables. Therefore, it is different from the general articles that put forward hypotheses and verify them. Thus, no hypotheses were made in our article. The robustness test regarding the convergence of conditional β is presented in the paper.

In the paper, we have made the following changes:

Line 274-288, we added “We use the Dagum Gini coefficient to study the regional differences in the development of renewable energy in China. It is different from the ordinary Gini coefficient. It can solve the limitations of the traditional Gini coefficient when decomposes the sources of income inequality and decomposes the overall inequality into three parts: intra-group differences, inter-group differences, and super-variable density differences. The spatial correlation of renewable energy development is analyzed using the Moran’s I. The distribution dynamics of renewable energy development are studied by using common nuclear density estimation methods. The σ convergence is used to measure whether the dispersion degree of per capita renewable energy power generation decreases over time, directly reflecting the change in absolute differences between regions. In the article, absolute β convergence does not require the control of other conditions, and it is analyzed whether all regions tend to the same steady state. The con-vergence of condition β requires control conditions to study whether each region tends to its own steady state. In addition, when we conducted the convergence of condition β, we carried out and passed the Wald test and LR test.”

Line 533-539, We conducted the Wald test and the LR test and passed the tests. “Table 9 reports the coefficient estimation results of conditional β convergence for per capita renewable energy generation. By observing the test results in table 9, we can see that the eastern, central, western and northeastern regions all pass the Wald test and LR test, and the SDM model is used for absolute β convergence analysis and conditional β convergence analysis for the eastern, central, western and northeastern regions. However, the whole country did not pass the Wald test, so the SEM model was used for convergence analysis.”

 

Comment 3. Moreover, while the structure of the results section has improved, interpretation remains shallow. Trends are presented without adequate critical comparison to prior studies or implications for regional energy strategies. The figures, though better formatted, still fall short in quality and clarity, so professional reprocessing is recommended. FIGURE 1! Make more professional and add labels properly to support your idea.

Responses 3: Thank you very much for your suggestions. We adopted them and made some modifications.

Regarding the issue you raised that Figure 1 is not professional enough, we have unified the color and format of all trend charts to make the charts in the entire article more standardized and aesthetically pleasing.

Considering your suggestion, we did not take into account the regional energy strategy of China in the original article. Therefore, the following supplements are made:

Line 628-641, we added “the core of China's regional energy strategy lies in adapting measures to local conditions and adopting classified policies, implementing differentiated layout and regional coordinated development, which coincides with the research of this article. On the one hand, China is driven by carbon peaking and carbon neutrality. On the other hand, due to energy security and regional balance, China's energy resources are unevenly distributed (for instance, the west is rich in wind, solar and hydropower, while the east relies on energy input). Therefore, it is necessary to optimize resource allocation through projects such as "West-to-East Power Transmission", reduce external dependence and enhance regional energy self-sufficiency. Based on resource endowments and development needs, China is divided into four major energy strategic regions. The western region serves as a base for renewable energy and the core of energy output. The eastern region promotes the transformation of energy consumption and technological innovation. The central region functions as an energy transmission hub and an industrial upgrading belt. The northeastern region realizes the energy trans-formation of old industrial bases and the clean heating. The implementation of the regional differentiated development strategy coincides with the research results of this paper.”

Line 642-645, Regarding policy recommendations, we added “implement spatially differentiated policy frameworks that account for regional resource endowments, such as establishing preferential feed-in tariffs for hydropower-rich southwestern provinces while prioritizing distributed solar incentives in eastern metropolitan areas.”

 

Comment 4. Comments on the Quality of English Language:

A professional language edit would help elevate the manuscript to publication standards. Overall, the study has potential, but more substantial revisions are needed to ensure it meets both scientific and editorial expectations.

Responses 4: Thank you very much for your suggestion. We have considered your suggestion and sought help from native English speakers to improve the words and sentences of the article to make it more natural and fluent. Thank you for your patience and tolerance.

Moreover, in order to make the paper more unified and professional in certain terms, we have made some changes.

For example, we changed "renewable energy generation" to "REG";

We changed "nuclear density estimation" to "kernel density estimation";

The expression methods of Moran’s index include Moran' I, Moran index, and Moran's index. In this article, we uniformly used Moran's I.

In accordance with international standards for the use of unit orders of magnitude, “1450 gigawatts (GW)” has been modified to “1.45 TW (terawatts)” (line 52-53)

To improve the accuracy of some language expressions, change “30 provinces” to “30 provincial-level administrative units” (line 221-222, line 354-355, line 359-360, line 578).

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

None

Author Response

Thank you for coordinating the review process of our manuscript “Research on the Distribution Dynamics and Convergence of Renewable Energy in China”. We appreciate the time and expertise you have dedicated to evaluating our work. While we note that no specific comments were provided in this round, we revised the manuscript according to the suggestions of other reviewers and stand ready to address any additional requirements that may arise in subsequent stages of the review process. Should further clarification or revisions be needed, please do not hesitate to contact us. We remain fully committed to meeting the journal’s publication standards.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

The detailed response to my last report is satisfactory, I thus recommend acceptance of the revised manuscript.

Comments on the Quality of English Language

The English could be improved to more clearly express the research.

Author Response

Comment: Comments on the Quality of English Language:

The English could be improved to more clearly express the research.

Responses: Thank you for your suggestions on our paper. We have considered your suggestion and sought help from native English speakers to improve the words and sentences of the article to make it more natural and fluent. Thank you for your patience and tolerance.

Moreover, in order to make the paper more unified and professional in certain terms, we have made some changes.

For example, we changed "renewable energy generation" to "REG";

We changed "nuclear density estimation" to "kernel density estimation";

The expression methods of Moran’s index include Moran's I, Moran index, and Moran's index. In this article, we uniformly used Moran's index.

In accordance with international standards for the use of unit orders of magnitude, “1450 gigawatts (GW)” has been modified to “1.45 TW (terawatts)” (line 52-53)

To improve the accuracy of some language expressions, change “30 provinces” to “30 provincial-level administrative units” (line 221-222, line 354-355, line 359-360, line 578).

Moreover, revised portion are marked in yellow in the paper. Again, thank you sincerely for your suggestion.

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

While the authors have clearly made thoughtful revisions and addressed many of the original concerns—particularly in strengthening the manuscript’s structure, refining the expression of novelty, and improving parts of the figures—there are still several important points within the Results and Data Visualization sections that require further attention before the work can be considered ready for publication.

The introduction continues to lack sufficient citations to support the claims made. This absence undermines the credibility and scholarly value of the work. Please ensure that all key assertions—especially those regarding previous studies, theoretical foundations, or contextual relevance—are properly supported with up-to-date and authoritative references. Strengthening the citation framework is essential to enhance the academic robustness and traceability of your argumentation

Regarding the robustness of the methodology, the inclusion of Wald and LR tests for conditional β convergence is a positive step. However, on its own, it does not fully resolve the concern about sensitivity. A simple but clear sensitivity check—such as varying regional classifications, time intervals, or excluding specific provinces—would be valuable. Including this either within the main results or as supplementary material would help demonstrate the stability and reliability of the conclusions.

In terms of figure presentation, Figures 1 and 2 still do not meet the expected level of professionalism. Some formatting issues remain, including inconsistent font sizes and axis labels. More importantly, the absence of standard deviation bars or confidence intervals limits the interpretability of the visual data. These elements are essential to convey variability and reinforce the strength of the findings.

Figures 4 through 6 also remain somewhat ambiguous. The current format does not clearly convey the spatial context, especially for international readers unfamiliar with China’s regional layout. A small contextual map, clearer regional labels, and a more consistent use of color would make a significant difference in clarity. This would not only enhance the visual appeal but also ensure the figures effectively communicate their intended message.

Additionally, while the results section is well-structured, it continues to be largely descriptive. It would benefit from a deeper comparative interpretation, especially by referencing recent literature from other countries dealing with similar regional disparities in renewable energy development. Even brief comparisons with recent Q1 studies (2022–2024) from countries like India, Brazil, or the US could enrich the discussion and broaden the international relevance of the study.

Lastly, although the English has been improved, there are still some dense or awkward constructions that could be smoothed out with a final light language edit—especially in the Discussion section, where clarity is crucial for communicating implications to a wider audience.

In summary, the authors have made meaningful progress and the manuscript is much closer to publication readiness. With further refinements to the figures, a brief sensitivity check, and some additional depth in comparative discussion, the paper would meet the quality expected for Sustainability. 

 

 

Author Response

We sincerely thank you for pointing out the problems existing in our article, such as insufficient supporting literature in the introduction section, inadequate explanation of the robustness test, issues with the consistency and professionalism of the figures used, and relatively shallow explanations in the conclusion section. We believe that with your help, our articles can be more professional, clear and easy to understand. We have also made specific responses and improvements to the suggestions you raised. The evaluation of this work is as follows:

Comment 1. The introduction continues to lack sufficient citations to support the claims made. This absence undermines the credibility and scholarly value of the work. Please ensure that all key assertions—especially those regarding previous studies, theoretical foundations, or contextual relevance—are properly supported with up-to-date and authoritative references. Strengthening the citation framework is essential to enhance the academic robustness and traceability of your argumentation.

Responses 1: Thank you for your valuable feedback. We acknowledge the importance of robust citations to anchor the claims in the introduction. Accordingly, we have revised the introduction to integrate authoritative and recent references (2019–2024) that substantiate the theoretical foundations and contextual relevance. Below are the revisions made to address this suggestion:

We added “Carbon neutrality should be incorporated into the socialist modernization strategy (He J, Li Z, Zhang X, et al., 2022).” (Line 31-33)

We have supplemented the data sources of China's installed capacity of renewable energy. We added “China Statistical Yearbook (2023）reported, by 2023, China's total installed capacity of renewable energy exceeded 1.45 TW (terawatts), accounting for about 35% of the world's total installed capacity. China's REG reached 2.7 trillion kilowatt-hours (TWh), accounting for 34 percent of the country's total power generation and 28 percent of global REG. Per capita installed renewable energy capacity is about 1.03 kilowatts (kW). Renewable energy generation per capita is about 1,914 kilowatt-hours (kWh).” (Line 54-59)

We have introduced the literature support of the influencing factors of the development of renewable energy in line 60-62. The specific modification is: “There are many factors affecting the development of renewable energy, including government policy support (Fatima et al.,2021; Ma et al.,2022; Monirul et al.,2022), in-vestment environment (Hassan et al.,2024), technological progress (Gielen et al.,2019) and market demand (Tan et al.,2023).”

We supplemented the literature on the impact of renewable energy on carbon emissions in line 86-89. The specific modification is: “Through these measures, not only can improve China's energy efficiency, ensure energy security, reduce dependence on traditional fossil fuels, but also effectively reduce carbon emissions (Yu et al.,2024; Chen et al.,2024; Liu et al.,2023), thereby helping to maintain the ecological balance of the earth.”

 

Comment 2. Regarding the robustness of the methodology, the inclusion of Wald and LR tests for conditional β convergence is a positive step. However, on its own, it does not fully resolve the concern about sensitivity. A simple but clear sensitivity check—such as varying regional classifications, time intervals, or excluding specific provinces—would be valuable. Including this either within the main results or as supplementary material would help demonstrate the stability and reliability of the conclusions.

Responses 2: Thank you for your constructive feedback on the robustness of our methodology. We appreciate the value of sensitivity checks (e.g., varying regional classifications, time intervals, or excluding specific provinces) in reinforcing conclusions. However, our study adheres to the official four-region classification (East, Central, West, Northeast) defined by China’s National Bureau of Statistics, which aligns with widely accepted frameworks for regional energy policy analysis. Modifying this classification would compromise comparability with existing literature and policy benchmarks. Of course, we also want to explain to you that the China Statistical Yearbook lacks the renewable energy data of the Tibet Autonomous Region (as explained in lines 65-66 of the manuscript), so the renewable energy power generation data in the western region is not particularly comprehensive.

The 2006–2021 timeframe was selected to capture critical phases of renewable energy policy evolution in China, including pre- and post-“dual carbon” target periods. Adjusting this interval might disrupt the coherence of policy impact analysis. Regarding province exclusion, our sample (30 provinces) already reflects minimal regional heterogeneity, and selective removal could bias regional representativeness.

 

Comment 3. In terms of figure presentation, Figures 1 and 2 still do not meet the expected level of professionalism. Some formatting issues remain, including inconsistent font sizes and axis labels. More importantly, the absence of standard deviation bars or confidence intervals limits the interpretability of the visual data. These elements are essential to convey variability and reinforce the strength of the findings.

Responses 3: Thank you for your rigorous feedback on improving the clarity and professionalism of our figures. We have implemented comprehensive revisions to address the formatting inconsistencies issue:

We ensured the uniformity of the font and labels. The vertical axes of Figure 1-3 were all in Times New Roman font to ensure that the font sizes of the titles, axis labels, and legends were consistent. We also adjusted the alignment of Figures 1-3 in the manuscript to ensure that the figures are neatly arranged. Furthermore, since there are no standard deviation data and confidence intervals for the Gini coefficients within and between groups, they cannot be provided in the figure. Figure 1-3 are as follows:

Figure 1. Variation trend chart of Gini coefficient in the region.

 

Figure 2. Trend chart of interregional Gini coefficient.

 

 

Figure 3. Global Moran’s I change.

 

Comment 4. Figures 4 through 6 also remain somewhat ambiguous. The current format does not clearly convey the spatial context, especially for international readers unfamiliar with China’s regional layout. A small contextual map, clearer regional labels, and a more consistent use of color would make a significant difference in clarity. This would not only enhance the visual appeal but also ensure the figures effectively communicate their intended message.

Responses 4: Thank you for pointing out that figure 4, figure 5 and figure 6 are quite similar. These three graphs are the kernel density curves of renewable energy power generation in the national, central and eastern regions, which we made using Matlab based on the data from 2006 to 2021. And the significance represented by the changes in the kernel density curve was analyzed in Line 462-480 of the manuscript. The analysis of the kernel density curve is as follows:

In figure 4-8, from the perspective of distribution, the main peak of the national kernel density curve is to the left, indicating that there are relatively many provinces with a low level of renewable energy development. From the distribution pattern, the height of the main peak decreases, which indicates that the concentration of per capita REG in each province at the peak decreases, and there is a certain degree of dispersion. As shown in Figure, at the beginning of the statistical period, the kernel density curves of the eastern region, the central region and the western region have "one main peak and one side peak", indicating that spatial polarization exists in these regions. However, at the end of the statistical period, the eastern region and the western region gradually evolve into a single main peak pattern, while the central region has "one main peak and one side peak", and the height of the side peak decreases. It shows that the spatial polarization phenomenon has a weakening trend. The reasons for the weakening of spatial polarization in the region may be the relatively similar resources and environment in the same region, government policy guidance, promotion and exchange of renewable energy development technology. In Figure, the kernel density curve in Northeast China is generally unimodal except for individual multi-modal phenomena in 2019, indicating that the development of renewable energy in Northeast China is relatively balanced, and the reason for the balanced development may be the similar resource environment and similar government policies in the three Northeast provinces.

The design of this study is based on the four major regional classifications (East, Central, West, and Northeast) officially divided by the National Bureau of Statistics. This classification has been widely used in the research of regional economy and energy policies in China. The eastern region includes all the eastern provinces of China (Beijing Municipality, Tianjin Municipality, Hebei Province, Shanghai Municipality, Jiangsu Province) Zhejiang Province, Fujian Province, Shandong Province, Guangdong Province, Hainan Province The central region includes all the central provinces of China (Shanxi Province, Anhui Province, Jiangxi Province, Henan Province, Hubei Province, Hunan Province); The western Region includes the various western provinces of China (Inner Mongolia Autonomous Region, Guangxi Province, Chongqing Municipality, Sichuan Province) Guizhou Province, Yunnan Province, Tibet Autonomous Region, Shaanxi Province, Gansu Province, Qinghai Province,  Ningxia Autonomous Region, Xinjiang Region The Northeast region includes all the provinces of China (Jilin Province, Heilongjiang Province).

 

 

Comment 5. Additionally, while the results section is well-structured, it continues to be largely descriptive. It would benefit from a deeper comparative interpretation, especially by referencing recent literature from other countries dealing with similar regional disparities in renewable energy development. Even brief comparisons with recent Q1 studies (2022–2024) from countries like India, Brazil, or the US could enrich the discussion and broaden the international relevance of the study.

Responses 5: Thank you for your valuable suggestions on the international relevance of the research and the depth of the results.

We have added a discussion on the differences in the development level of global renewable energy in 4.1.1 of the manuscript. There are also differences REG worldwide. North American and Asian countries such as China and Japan have demonstrated remarkable achievements in renewable energy development, whereas most countries in South America and Africa remain at a relatively low level; Secondly, the imbalance in the development of global renewable energy primarily originates from regional structural differences, and the global gap in per capita renewable energy production is narrowing (Chen, 2025). (Line 437-442)

 

Comment 6. Lastly, although the English has been improved, there are still some dense or awkward constructions that could be smoothed out with a final light language edit—especially in the Discussion section, where clarity is crucial for communicating implications to a wider audience.

Responses 6: Thank you for pointing out again that the English editing of our manuscript is not concise and easy to understand.

We pay more attention to the correct use of tenses in the article and reduce the use of passive voice to make the article more readable.

We have made the following changes:

1.Line 21-22

Before: “thus we can promote the realization of the "dual carbon" goal more efficiently.”

After: “thus we can promote a more efficient realization of the "dual carbon" goal.”

2.Line 30-40

Before: “The construction of these power generation facilities needs to be adapted to local conditions”.

After: “The construction of these power generation facilities needs to adapt to local conditions”.

3.Line 82-84:

Before: “which is helpful to formulate corresponding policies and measures to promote the rational development and utilization of renewable energy.”

After: “It is helpful to formulate corresponding policies and measures to promote the rational development and utilization of renewable energy.”

4.Line 277-286.

Before: “We use the Dagum Gini coefficient to study the regional differences in the development of renewable energy in China. It is different from the ordinary Gini coefficient. It can solve the limitations of the traditional Gini coefficient when decomposes the sources of income inequality and decomposes the overall inequality into three parts: intra-group differences, inter-group differences, and super-variable density differences. The spatial correlation of renewable energy development is analyzed using the Mo-ran’s I. The distribution dynamics of renewable energy development are studied by using common kernel density estimation methods. The σ convergence is used to measure whether the dispersion degree of per capita renewable energy power generation decreases over time, directly reflecting the change in absolute differences between regions. In the article, absolute β convergence does not require the control of other conditions, and it is analyzed whether all regions tend to the same steady state.”

After: “We used the Dagum Gini coefficient to study the regional differences in the development of renewable energy in China. It is different from the ordinary Gini coefficient. It can solve the limitations of the traditional Gini coefficient when decomposes the sources of income inequality and decomposes the overall inequality into three parts: intra-group differences, inter-group differences, and super-variable density differences. We analyzed the spatial correlation of renewable energy development by using the Moran’s I. We studied the distribution dynamics of renewable energy development by using kernel density estimation methods. We used the σ convergence to measure whether the dispersion degree of per capita renewable energy power generation decreases over time, directly reflecting the change in absolute differences between regions. In the article, absolute β convergence does not require the control of other conditions, and we analyzed whether all regions tend to the same steady state.”

5.Line 344-345

Before: “Where, REG data from the ‘China Electricity Yearbook’, ‘China Electricity Statis-tical Yearbook’.”

After: “REG data is from the ‘China Electricity Yearbook’, ‘China Electricity Statistical Yearbook’.”

6.Line 355-356

Before: “This paper is based on the provincial panel data of 30 provincial-level administrative units in China from 2006 to 2021. The basic characteristics of per capita REG, REG ratio, per capita installed renewable energy capacity, per capita GDP, urbanization rate, environmental regulation and per capita coal consumption are shown in table 2 below.”

After: “This paper bases on the provincial panel data of 30 provincial-level administrative units in China from 2006 to 2021. The table 2 below shows the basic characteristics of per capita REG, REG ratio, per capita installed renewable energy capacity, per capita GDP, urbanization rate, environmental regulation and per capita coal consumption.”

7.Line 369

Before: “The Gini coefficient values in the region are shown in table 3.”

After: “The table 3 shows the Gini coefficient values in the region.”

8.Line 394

Before: “Inter-regional Gini coefficients are shown in table 4.”

After: “The table 4 shows inter-regional Gini coefficients.”

9.Line 426-427

Before: “The difference contribution rate is composed of intra-group difference contribution rate and inter-group difference contribution rate.”

After: “The difference contribution rate composes intra-group difference contribution rate and inter-group difference contribution rate.”

10.Line 586-589

Before: “Secondly, the kernel density estimation method is used to analyze the distribution dynamics of REG in China and four regions. Finally, the spatial correlation is analyzed using the Moran’s I, and then the convergence is tested by σ convergence and spatial β convergence.”

After: “We used the kernel density estimation method to analyze the distribution dynamics of REG in China and four regions. Finally, we used the spatial correlation by using the Moran’s I, and then we tested the convergence by σ convergence and spatial β convergence.”

11.Line 666-668

Before: “so as to invest more funds in the production of renewable energy and increase the re-search and development of renewable energy, so as to improve the development efficiency of renewable energy.”

After: “so as to invest more funds in the production of renewable energy, increase the research and development of renewable energy and improve the development efficiency of renewable energy.”

Author Response File: Author Response.pdf