Rethinking Regional High-Quality Development Pathways from a Carbon Emission Efficiency Perspective
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe manuscript assessed the carbon emission efficiency (CEE) in the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA), and constructed a comprehensive influencing factor index to analyze and identify the key influence factors of CEE. The structure is clear and well organized. The results and conclusions are significant for the carbon reduction for the BTHUA. However, there are still some minor revisions need to consider before publication.
1. As for the abstract, I recommend that the authors added some description about the CEE of the 13 cities for the result section.
2. “Carbon reduction” and “urban agglomeration” can be considered to put in the keywords.
3. Please uniform the terminologies in the manuscript, such as carbon emissions and carbon emission, nature- based solutions.
4. In Line 305, the word “varitions” should be “variations”.
5. Fig 7 (line 428) should be “Figure 7”. Fig 8 (line 450) should be “Figure 8”.
6. As for Section 6.3, the first policy suggestion is to reduce the fossil fuel energy consumption. The related description should be polished.
7. There are still minor mistakes for the spelling and grammar in the current manuscript. Please further check and polish the language.
Comments on the Quality of English LanguageThere are still minor mistakes for the spelling and grammar in the current manuscript. Please further check and polish the language.
Author Response
Response to Comments from Reviewer #1
We first want to thank reviewer #1 for his/her careful reading of our manuscript. In total, the reviewer had 7 comments on our manuscript. We have responded and incorporated the revisions into our revised manuscript.
Comments:
The manuscript assessed the carbon emission efficiency (CEE) in the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA), and constructed a comprehensive influencing factor index to analyze and identify the key influence factors of CEE. The structure is clear and well organized. The results and conclusions are significant for the carbon reduction for the BTHUA. However, there are still some minor revisions need to consider before publication.
Comment 1:
As for the abstract, I recommend that the authors added some description about the CEE of the 13 cities for the result section.
Response: Thanks for your comments. We have added a brief description about the CEE among the 13 cities in the abstract section. The description has been embodied in the revised manuscript as follows.
Line 26-27:
……The average CEE in Langfang was lowest, while that in Tangshan was highest.……
Comment 2:
“Carbon reduction” and “urban agglomeration” can be considered to put in the keywords.
Response: Thanks for your comments. We really think they are crucial, so we’ll take your advice into consideration. We have added it into the key words.
Comment 3:
Please uniform the terminologies in the manuscript, such as carbon emissions and carbon emission, nature- based solutions.
Response: Thanks for your comments. It is really reasonable that we ought to uniform our terminologies in the manuscript. We have checked the whole manuscript carefully. And we decided to use “carbon emissions” to uniform carbon emissions and carbon emission.
Comment 4:
In Line 305, the word “varitions” should be “variations”.
Response: Thanks for your comments. We have already corrected it. We apologize for our misspelling.
Comment 5:
Fig 7 (line 428) should be “Figure 7”. Fig 8 (line 450) should be “Figure 8”.
Response: Thanks for your comments. We have corrected it in time.
Comment 6:
As for Section 6.3, the first policy suggestion is to reduce the fossil fuel energy consumption. The related description should be polished.
Response: Thanks for your comments. It is significant to polish the description. We have improved the expression of reducing the fossil fuel energy consumption. The description has been embodied in the revised manuscript as follows.
Line 478-482:
Firstly, reducing fossil fuel consumption can directly reduce carbon emissions, and make negative impacts on CEE. Replacing fossil energy with clean and renewable sources are also valid pathways to improve CEE. Reducing carbon emission sources can promote the decoupling of carbon emissions and high-density fossil energy from economic growth.
Comment 7:
There are still minor mistakes for the spelling and grammar in the current manuscript. Please further check and polish the language.
Response: Thanks for your comments. We have checked the whole manuscript and made revisions for the spelling mistakes. Moreover, Native English speakers have polished the whole manuscript. The specific modifications are embodied in the revised manuscript.
Reviewer 2 Report
Comments and Suggestions for AuthorsRethinking regional high-quality development pathways from a carbon emission efficiency perspective
The paper builds a stochastic frontier analysis model to assess the carbon emissions intensity (CEE) and conducts a case study in the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA) region. The authors develop an index to analyze key factors influencing CEE. The results show a list of factors that have a negative effect on the CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, energy intensity, and others. A list of several other factors have a positive effect on CEE: GDP per capita, urbanization level, and the proportion of the tertiary sector.
The paper makes a significant contribution to the literature. It needs a substantial English language edit by a native English speaker.
1) Please, consider energy efficiency conversion as a factor.
2) Can the authors put their discussion in the context of achieving the carbon emissions reduction targets of the 12th Five-Year Plan?
3) Could the authors give a better explanation for the outlier cities, such as LF-Langfang and TJ-Tianjin.
4) Green growth and innovation have been proven to play a role in emissions reduction. However, the article pays almost no attention to these factors. Could the authors try patents in new technologies in the computation of the index.
Comments on the Quality of English Language
Please, see the report.
Author Response
Response to Comments from Reviewer #2
We first want to thank reviewer #2 for his/her careful reading of our manuscript. In total, the reviewer had 4 comments on our manuscript. We have responded and incorporated the revisions into our revised manuscript.
Comments:
The paper builds a stochastic frontier analysis model to assess the carbon emissions intensity (CEE) and conducts a case study in the Beijing-Tianjin-Hebei Urban Agglomeration (BTHUA) region. The authors develop an index to analyze key factors influencing CEE. The results show a list of factors that have a negative effect on the CEE, including carbon emissions per capita, employment per ten thousand people, total assets per capita, energy intensity, and others. A list of several other factors have a positive effect on CEE: GDP per capita, urbanization level, and the proportion of the tertiary sector. The paper makes a significant contribution to the literature. It needs a substantial English language edit by a native English speaker.
Response: Thanks for your comments. We will try our best to polish our language to express our research like a native English speaker as possible as we can. And thank you so much for your compliments!
Comment 1:
Please, consider energy efficiency conversion as a factor.
Response: Thanks for your comments. Energy efficiency conversion is factually a crucial factor when using energy and make economic growth. However, we haven’t used the energy efficiency conversion as a specific index. Actually, we used Carbon emissions per capita ( ) to represent the technological level in the influencing factor analysis, and use Energy consumption per unit of GDP ( ) to represent energy intensity. indicates technological level in the carbon production process, including energy efficiency conversion. can be obtained through carbon emissions and GDP. In future research, we will consider how to use more accurate indicators to represent energy efficiency conversion, and explore the relationship between CEE and energy efficiency conversion. Moreover, we have added related manuscript about energy efficiency conversion in the discussion section.
Comment 2:
Can the authors put their discussion in the context of achieving the carbon emissions reduction targets of the 12th Five-Year Plan?
Response: Thanks for your comments. We have added the targets of 12th Five-Year Plan in the discuss section in the revised manuscript.
Comment 3:
Could the authors give a better explanation for the outlier cities, such as LF-Langfang and TJ-Tianjin.
Response: Thanks for your comments. Langfang is a prefecture-level city in Hebei Province. Tianjin is a municipality directly under the Central Government. As shown in the Figure 4-6, we found that Beijing, Tianjin and Langfang has the large range of CEE values. This result is mainly due to the choice and values of input and output variables. We can't explain exactly which variable is causing it. However, after the model is verified, this does not affect the scientific nature of the results.
Comment 4:
Green growth and innovation have been proven to play a role in emissions reduction. However, the article pays almost no attention to these factors. Could the authors try patents in new technologies in the computation of the index.
Response: Thanks for your comments. We constructed the influencing factor index including economic level, technological level, input level, urbanization level, industrial structure, energy intensity, level of opening up, and government intervention. We use the carbon emissions per capita to represent the technological level through literature review. Thereby, we didn’t consider some other indexes in the influencing factors. In the future, we will discuss more indexes of more comprehensive aspects to analyze what influences CEE.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe title of the article is current, it falls within the eco-efficiency trend, which is a particularly important problem due to the climate challenges that the entire modern world is currently struggling with.
However, the article's abstract does not directly disclose the purpose of the article or the research hypotheses. I suggest including the following sentence "The purpose of this publication is ... (specific goals may also be indicated)". In addition, for the full readability of the article, I suggest including the following sentence "In the analyses discussed, the following main hypothesis was adopted (necessarily related to the goal) and if there are specific goals, link the specific hypotheses to them"
There are goals, but hypotheses are missing!!!
"GDP increased from 9.4977 × 1012 yuan in 2000 to 8.4479 × 1013 yuan in 2019, with a growth rate of 789.47%." Are these values correct? I have doubts!!! Usually, we refer the GDP value and growth rate to a year and not, as in the work, to 20 consecutive years. I understand that it is probably about determining some trend, if so, a trend line type construction should have been used. "The industrial structure has changed significantly. The GDP of the industrial services sector increased from 2.1749 × 1012 yuan in 2000 to 2.96634 × 1013 yuan in 2019, and the corresponding share increased from 47.96% to 81.25%. "
Why were the insignificant variables lnK and lnL left in Table 3? I suggest removing the statistically insignificant variables from the model. Similarly, in Table 4, the variables popit and ind2it are statistically insignificant variables, leaving such variables in the model distorts its image.
In the conclusion, several dry facts resulting from the calculations are indicated, there is no even a brief polemic with other scientific reports. Moreover, in this part of the work there should be a clear reference to the objectives of the analyses and hypotheses (I did not notice any research hypotheses in the work).
Comments for author File: 
Comments.pdf
Author Response
Response to Comments from Reviewer #3
We first want to thank reviewer #3 for his/her careful reading of our manuscript. In total, the reviewer had 5 comments on our manuscript. We have responded and incorporated the revisions into our revised manuscript.
Comments:
The title of the article is current, it falls within the eco-efficiency trend, which is a particularly important problem due to the climate challenges that the entire modern world is currently struggling with.
Comment 1: However, the article's abstract does not directly disclose the purpose of the article or the research hypotheses. I suggest including the following sentence "The purpose of this publication is ... (specific goals may also be indicated)". In addition, for the full readability of the article, I suggest including the following sentence "In the analyses discussed, the following main hypothesis was adopted (necessarily related to the goal) and if there are specific goals, link the specific hypotheses to them". There are goals, but hypotheses are missing!!!
Response: Thanks for your comments. We have added the purpose of the article in the introduction section. The description has been embodied in the revised manuscript as follows.
Line 72-73:
The purpose of this study is to evaluate the CEE of cities in the BTHUA and identify key influencing factors, supporting low-carbon and economic goals.
As for the hypotheses, we analyzed the CEE and the influencing factors of CEE from literature review. In this paper, we first built the SFA model to estimate CEE, and explore the impact characteristics of the influencing factors. This paper is an engineering paper, not in the social sciences. In this study, we can’t forecast the variations of CEE in the BTHUA ahead of time. We mainly review the methods and build the model to assess CEE. If the model results pass the verification, we believe that the results are credible and can be further analyzed. Therefore, we didn’t summarize the hypotheses in the introduction section before conducting empirical research. However, what you suggest are absolutely right, we will pay more attentions to the scientific progress of conducting the researches by hypotheses and proofs in the future. Thank you for your suggestion.
Comment 2:
"GDP increased from 9.4977 × 1012 yuan in 2000 to 8.4479 × 1013 yuan in 2019, with a growth rate of 789.47%." Are these values correct? I have doubts!!! Usually, we refer the GDP value and growth rate to a year and not, as in the work, to 20 consecutive years. I understand that it is probably about determining some trend, if so, a trend line type construction should have been used. "The industrial structure has changed significantly. The GDP of the industrial services sector increased from 2.1749 × 1012 yuan in 2000 to 2.96634 × 1013 yuan in 2019, and the corresponding share increased from 47.96% to 81.25%. "
Response: Thanks for your comments. The economic data come from the official government-published statistical yearbook. We have rechecked the data and The GDP value data is right. We have deleted the words “with a growth rate of 789.47%”, and “and the corresponding share increased from 47.96% to 81.25%.” in the original manuscript. Figure 1 shows the GDP change from 2000 to 2019 in the BTHUA. Figure 2 shows the industrial structure in the BTHUA from 2000 to 2019.
Figure 1. GDP in the BTHUA from 2000 to 2019.
Figure 2. Industrial structure in the BTHUA from 2000 to 2019.
Comment 3:
Why were the insignificant variables lnK and lnL left in Table 3? I suggest removing the statistically insignificant variables from the model. Similarly, in Table 4, the variables popit and ind2it are statistically insignificant variables, leaving such variables in the model distorts its image.
Response: Thanks for your comments. We understand your suggestion. However, in order to ensure the completeness of the results, we still present the full parametric results. If you strongly request to delete these insignificant variables, we can also delete them in the next version.
Comment 4:
In the conclusion, several dry facts resulting from the calculations are indicated, there is no even a brief polemic with other scientific reports. Moreover, in this part of the work there should be a clear reference to the objectives of the analyses and hypotheses (I did not notice any research hypotheses in the work).
Response: Thanks for your comments. The purpose of this study is to evaluate the CEE of cities in the BTHUA and identify key influencing factors, supporting low-carbon and economic development goals. In the results, we found that the mean value of CEE among the 13 cities fluctuated and increased during 2000-2019. Input-related influencing factors had significant effects on CEE, including the carbon emissions per capita, employment per ten thousand people and total assets per capita. Moreover, Urbanization level had a significant positive effect on CEE. Industrial structure upgrading can help to increase CEE. Energy intensity, level of openness, and government intervention were all negative influencing factor parameters. All these results indicated that the development is still at a stage of heavy reliance on a large amount of human and material resources in the BTHUA. We have illustrated why there isn’t a hypothesis in the paper in the response to comment 1. Moreover, we have made a comparable analysis with other studies. The results must be scientific and can be used as a reference for policy making.
Author Response File: Author Response.pdf
