Research on Carbon Emissions and Influencing Factors of Residents’ Lives in Hebei Province

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This paper empirically estimates the drivers of carbon emissions for part of China.  Then, the paper uses its estimated model to 'predict' the future path of carbon emissions.  The study is of obvious importance.

 

My only real comment is that there are many things that go into the carbon emissions, including the technology adopted, the industries present, and even trade and migration patterns.  I do not think the paper needs to consider everything in its analysis.  However, some discussion of these other factors might help broaden the audience for the paper.

In particular, one of the main drivers of emissions considered in the paper is the population size.  However, most of the literature that I have seen considers the demographic composition, too.  I think the basic idea is that young and middle-aged people drive more, etc.  I have listed several papers related to this below.  I think this point should at least be discussed, as China is aging rapidly.  Maybe it would not be too hard to include in the analysis in a simple way.  Projections for the age distribution are probably available, although, of course, fertility and migration patterns are rapidly changing in China.

 

Related Papers:

Li, Shijie, and Chunshan Zhou. "What are the impacts of demographic structure on CO2 emissions? A regional analysis in China via heterogeneous panel estimates." Science of the Total Environment 650 (2019): 2021-2031.

 

Wang, Yong, et al. "Influencing factors and decoupling elasticity of China’s transportation carbon emissions." Energies 11.5 (2018): 1157.

 

Wang, Fei, et al. "Decomposition analysis of carbon emission factors from energy consumption in Guangdong Province from 1990 to 2014." Sustainability 9.2 (2017): 274.

LUGAUER, S., JENSEN, R. and SADLER, C. (2014), AN ESTIMATE OF THE AGE DISTRIBUTION'S EFFECT ON CARBON DIOXIDE EMISSIONS. Economic Inquiry, 52: 914-929.

Zhu, Xiaoping, and Rongrong Li. "An analysis of decoupling and influencing factors of carbon emissions from the transportation sector in the Beijing-Tianjin-Hebei Area, China." Sustainability 9.5 (2017): 722.

 

Guo, Wen, Tao Sun, and Hongjun Dai. "Effect of population structure change on carbon emission in China." Sustainability 8.3 (2016): 225.

 

Li, Weidong, Xin Qi, and Xiaojun Zhao. "Impact of population aging on carbon emission in China: A panel data analysis." Sustainability 10.7 (2018): 2458.

 

Yuan, Bin, et al. "The degree of population aging and living carbon emissions: Evidence from China." Journal of Environmental Management 353 (2024): 120185.

 

Basso, Henrique S., Richard Jaimes, and Omar Rachedi. "Demographics and emissions: the life cycle of consumption carbon intensity." Oxford Bulletin of Economics and Statistics (2022).

 

Rauscher, Michael. "Demographic change and climate change." Environment and Development Economics 25.1 (2020): 5-20.

 

Bin Yuan, Yuping Zhong, Shengsheng Li, Yihang Zhao, The degree of population aging and living carbon emissions: Evidence from China, Journal of Environmental Management, 10.1016/j.jenvman.2024.120185, 353, (120185), (2024)

Comments on the Quality of English Language

The English is fine.  Some editing is required before it could be published.

Author Response

Comments 1: This paper empirically estimates the drivers of carbon emissions for part of China.  Then, the paper uses its estimated model to 'predict' the future path of carbon emissions.  The study is of obvious importance.

My only real comment is that there are many things that go into the carbon emissions, including the technology adopted, the industries present, and even trade and migration patterns.  I do not think the paper needs to consider everything in its analysis.  However, some discussion of these other factors might help broaden the audience for the paper.

In particular, one of the main drivers of emissions considered in the paper is the population size.  However, most of the literature that I have seen considers the demographic composition, too.  I think the basic idea is that young and middle-aged people drive more, etc.  I have listed several papers related to this below.  I think this point should at least be discussed, as China is aging rapidly.  Maybe it would not be too hard to include in the analysis in a simple way.  Projections for the age distribution are probably available, although, of course, fertility and migration patterns are rapidly changing in China.

Response 1: Thank you for pointing this out and providing us with relevant literature as a reference. We agree with that comment. Therefore, we added a discussion on the influence of population aging on carbon emissions to the LMDI analysis results and inserted two references at the same time. Added content in the revised manuscript 13 pages, lines 375-381.

The specific changes are as follows:

According to the results of the LMDI analysis, the population size factor has an increasing effect on the direct carbon emissions and indirect carbon emissions of residents in Hebei Province. However, the population growth rate in Hebei Province has decreased, and even negative growth may occur, which is bound to lead to an aging population. Previous research has demonstrated an inverse U-shaped link between population structure and carbon emissions from residents[37]; that is, changes in the influence of population size may result from a deeper aging of the population[38].

37.   Li, W.; Qi, X.; Zhao, X., Impact of Population Aging on Carbon Emission in China: A Panel Data Analysis. Sustainability 2018, 10, (7), 2458-2458.

38.   Lugauer, S.; Jensen, R.; Sadler, C., An estimate of the age distribution's effect on carbon dioxide emissions. Economic Inquiry 2014, 52, (2), 914-929.

Comments 2: The English is fine.  Some editing is required before it could be published.

Response 2: Thanks for your suggestion. We have tried our best to polish the language in the revised manuscript.

Reviewer 2 Report

Comments and Suggestions for Authors

* Abstract Revision Needed: The current abstract employs an unconventional phraseology, such as "The article initially employs," which may distract from the scholarly tone expected in academic publications. More critically, the abstract fails to clearly articulate the research gap that this study aims to address. A revision should outline the research problem and specify the gap in the existing literature that this work proposes to fill.

* Clarity of Research Gap: The manuscript does not adequately identify or articulate a clear research gap. For the study to contribute effectively to the existing body of knowledge, it should delineate how this research advances or challenges current understanding in the field. 

* Relevance to Academic Interest: The focus on a specific region, while potentially valuable, lacks a clear justification for its academic relevance. The manuscript should provide a robust argument as to why this particular regional focus presents a unique opportunity for scholarly inquiry. 

* Theoretical Framework: The current approach of the paper leans towards providing managerial or policy recommendations, which, while practical, may not sufficiently contribute to theoretical development. It is advisable for the paper to more deeply engage with relevant theoretical frameworks, integrating them throughout the analysis to bolster the academic contribution of the work. This theoretical grounding would enhance the study's utility not just for practitioners but for scholars seeking to build upon the theoretical aspects of the field.

I hope these points assist in refining the paper to meet the publication standards of your esteemed journal. Each suggestion is aimed at strengthening the scholarly impact and theoretical contribution of the research.

Author Response

Comments 1: Abstract Revision Needed: The current abstract employs an unconventional phraseology, such as "The article initially employs," which may distract from the scholarly tone expected in academic publications. More critically, the abstract fails to clearly articulate the research gap that this study aims to address. A revision should outline the research problem and specify the gap in the existing literature that this work proposes to fill.

Response 1: Thank you for pointing that out. We agree with that comment. Therefore, we first revised the expression of the abstract from "The article initially employs" to "The first part of the article", and then added the problems that this study aims to solve in the abstract. The addition in the revised version is on page 1, lines 9-12. Add details as follows:

The standard of living has significantly risen along with the ongoing economic progress, but CO₂ emissions have also been rising. The reduction of CO₂ resulting from the daily activities of residents has become a crucial priority for every province. A relevant study on the carbon emissions of Hebei Province residents was done for this publication.

Comments 2: Clarity of Research Gap: The manuscript does not adequately identify or articulate a clear research gap. For the study to contribute effectively to the existing body of knowledge, it should delineate how this research advances or challenges current understanding in the field.

Response 2: Thank you for pointing that out. We agree with that comment. Therefore, in the introduction, we point out the insufficiency of the existing residential carbon emission and explain the contribution of this study to the field of residential carbon emission. The addition in the revised version is on page 2, lines 85-88. Add details as follows:

There is a dearth of studies on the prediction of residents' living carbon emissions, and the majority of publications on the subject analyze influencing variables. As a result, based on the investigation of the factors impacting residents' living carbon emissions, this study forecasts the trend in carbon emissions.

Comments 3: Relevance to Academic Interest: The focus on a specific region, while potentially valuable, lacks a clear justification for its academic relevance. The manuscript should provide a robust argument as to why this particular regional focus presents a unique opportunity for scholarly inquiry.

Response 3: Thank you for pointing that out. We agree with that comment. Therefore, in the introduction, we expounded on the comprehensive reasons for carbon emissions, population status, and emission reduction targets of Hebei Province, selected this province. The addition in the revised version is on page 2, lines 89-97. Add details as follows:

Since the implementation of the integration of Beijing, Tianjin, and Hebei in 2014, the economy of Hebei Province has developed rapidly, and the total amount of carbon dioxide emissions has been ranked second in the country all year round. The results of the seventh census of Hebei Province in 2020 show that the total population of the province has reached 74.61 million. To effectively reduce carbon emissions and achieve sustainable development, this study focuses on the influencing variables and trend analysis of carbon emissions of inhabitants in Hebei Province. The accomplishment of China's 2030 carbon peak and 2060 carbon neutral aim is very significant from a scientific and practical standpoint.

Comments 4: Theoretical Framework: The current approach of the paper leans towards providing managerial or policy recommendations, which, while practical, may not sufficiently contribute to theoretical development. It is advisable for the paper to more deeply engage with relevant theoretical frameworks, integrating them throughout the analysis to bolster the academic contribution of the work. This theoretical grounding would enhance the study's utility not just for practitioners but for scholars seeking to build upon the theoretical aspects of the field.

Response 4: Thank you for pointing that out. We agree with that comment. Therefore, we add corresponding emission reduction strategies and existing individual behavior emission reduction evidence to each conclusion of the paper in order to improve its practicability. Additions are placed on pages 16, lines 492-494, and on pages 17, 502-508. Add the specific content as:

Thus, the use of direct energy by inhabitants and expanding the use of clean energy should be the main priorities of Hebei Province's residential sector's emission reduction assignment.

According to a report, shared electric bicycles cut 54.50gCO₂ per kilometer and shared bicycles reduce 48.70gCO₂ per kilometer after weighted calculations. It makes clear how residents' daily lives may reduce carbon emissions by using electric and shared bicycles, and it offers a useful model for the advancement of environmentally friendly transportation. Residents ought to modify their consumption patterns and endeavor to embrace a low-emission way of living.

 

Reviewer 3 Report

Comments and Suggestions for Authors

 

1. The introduction section should provide a comprehensive overview of the current research on which aspects have been studied in the calculation of carbon emissions from residents' lives, rather than just stating that industrial construction has conducted carbon emission calculations while residents' lives has not, which is the research significance of this article.

2. Why is the LMDI decomposition method used to analyze the influencing factors of carbon emissions from residents' lives? What are the advantages compared with other methods?

3. Why is the LEAP Model used to predict carbon emissions from residents' lives? What are the advantages compared with other methods?

4. The conclusion and suggestion section seem to apply to any article, and it does not provide targeted recommendations based on the results of the above LMDI. It could further analyze how the findings in other studies can be applied to carbon emission reduction strategies in Hebei Province. The key is that this part only contains suggestions, without summarizing and concluding the entire paper. Moreover, the author should add empirical data to show how various low-carbon measures affect the quantitative results of carbon emissions from residents' lives, and possibly include some successful cases to enhance persuasiveness.

5. The paper has cited some relevant studies, but it seems that these references have not been deeply discussed in combination with the situation in Hebei Province.

6. The paper abstract did not elaborate on the specific calculation results and prediction results of carbon emissions.

7. It is suggested to analyze the differences in the adoption of low-carbon technologies in different regions of Hebei Province and how these differences affect carbon emissions.

8. In the analysis of impact factor, further explore the role of education, policy incentives and changes in consumer behavior in reducing carbon emissions of residents, except for technological progress.

Comments on the Quality of English Language

Moderate editing of English language required.

Author Response

Comments 1: The introduction section should provide a comprehensive overview of the current research on which aspects have been studied in the calculation of carbon emissions from residents' lives, rather than just stating that industrial construction has conducted carbon emission calculations while residents' lives have not, which is the research significance of this article.

Response 1: Thank you for pointing that out. We agree with that comment. Therefore, in the introduction, we summarized the current research status of residential carbon emissions and pointed out that the current research focuses on the analysis of influencing factors, and the prediction content is relatively small, reflecting the significance of this study. The addition in the revised version is on page 1, lines 78-88. Add details as follows:

The research on the carbon emissions of residents' lives. Markaki et al studied the influencing factors of Greek household carbon footprint from 1995 to 2012. Muhammad et al. researched how the population, economic growth, and urbanization of SAARC countries affected the carbon emissions of their residents. Trotta found that household consumption carbon emissions are affected by many factors, such as family size, income level, technological progress, etc. Nie et al. measured household consumption carbon emissions through questionnaires and analyzed relevant influencing factors There is a dearth of studies on the prediction of residents' living carbon emissions, and the majority of publications on the subject analyze influencing variables. As a result, based on the investigation of the factors impacting residents' living carbon emissions, this study forecasts the trend in carbon emissions.

Comments 2: Why is the LMDI decomposition method used to analyze the influencing factors of carbon emissions from residents' lives? What are the advantages compared with other methods?

Response 2: Thank you for pointing that out. We agree with the recommendation to increase the advantages of the LMDI approach. Therefore, when we introduced the LMDI method in this paper, we restated it and increased the advantages of the LMDI method. The position in the revised version is on page 4, lines 137-148. The content is restated as:

Decomposition analysis is a mainstream method for quantitative analysis of the contribution of CO₂ emission factors. The commonly used decomposition methods include exponential decomposition analysis (IDA) and structural decomposition analysis (SDA). Since IDA is based on terminal output data, it is easier to use smaller data samples for analysis. An example of an IDA version is the Logarithmic Mean Divisia Index (LMDI, a time-series-based decomposition technique with few variables. Furthermore, in contrast to alternative decomposition techniques, LMDI is simple to formulate, capable of efficiently resolving residual issues in the decomposition process, and yielding more accurate and persuasive decomposition results. Furthermore, the calculation process is reasonably easy to comprehend. Additive and multiplicative decomposition are the two primary LMDI techniques. This research uses LMDI additive factor decomposition since it is a simple and intuitive method of additive decomposition.

Comments 3: Why is the LEAP Model used to predict carbon emissions from residents' lives? What are the advantages compared with other methods?

Response 3: Thank you for pointing that out. We agree with the recommendation to increase the benefits of the LEAP model. Therefore, when we introduced the LEAP model in this article, we added the advantages of the LEAP model and the data characteristics of carbon emissions of Hebei residents. The addition in the revised version is on page 6, lines 215-220. Add details as follows:

The LEAP model can not only conveniently process the input of time series, but also effectively carry out complex scenario analysis. In addition, the LEAP model system has a huge underlying emission factor database and energy system analysis module. These advantages are just in line with the needs of residents’ carbon emission prediction. Residents’ lives involve not only energy modules, but also non-energy modules, and the underlying data is numerous, which is more matched with the LEAP model.

Comments 4: The conclusion and suggestion section seems to apply to any article, and it does not provide targeted recommendations based on the results of the above LMDI. It could further analyze how the findings in other studies can be applied to carbon emission reduction strategies in Hebei Province. The key is that this part only contains suggestions, without summarizing and concluding the entire paper. Moreover, the author should add empirical data to show how various low-carbon measures affect the quantitative results of carbon emissions from residents' lives, and possibly include some successful cases to enhance persuasiveness.

Response 4: Thank you for pointing that out. We agree with that comment. Therefore, we have made changes in the conclusions and recommendations. The summary of the full paper is added, suggestions are put forward based on the analysis results, and empirical evidence on the quantification of carbon emission reduction in residents' travel is listed to enhance persuasion. The addition in the revised version is on page 16, lines 484 to page 17, lines 513. Add details as follows:

This study takes the carbon emissions of residents in Hebei Province as the research object. Firstly, it calculates the carbon emissions of residents’ lives, then constructs the LMDI model for factor analysis, and finally constructs the LEAP model and scenario analysis method to predict the trend analysis of residents’ carbon emissions in Hebei Province.

The findings indicate that between 2005 and 2020, the carbon emissions of Hebei Province residents would increase. When looking at trends in change, direct carbon emissions have increased the most, whereas indirect carbon emissions have been steadily declining since 2012. When it comes to contribution, direct carbon emissions make up a larger portion than indirect carbon emissions. Thus, the use of direct energy by inhabitants and expanding the use of clean energy should be the main priorities of Hebei Province's residential sector's emission reduction assignment.

The results show that in the analysis of the influencing factors of residents’ carbon emissions, energy consumption intensity, income level, and population size are the factors that promote the increase of direct carbon emissions, and consumption tendency is the factor that inhibits direct carbon emissions. Consumption structure, economic level, and population size are the factors that promote the increase of indirect carbon emissions, while energy structure and energy consumption intensity are the factors that inhibit indirect carbon emissions. Therefore, the carbon emission reduction of residents in Hebei Province should focus on energy consumption intensity and consumption structure. According to a report, shared electric bicycles cut 54.50gCO₂ per kilometer and shared bicycles reduce 48.70gCO₂ per kilometer after weighted calculations. It makes clear how residents' daily lives may reduce carbon emissions by using electric and shared bicycles, and it offers a useful model for the advancement of environmentally friendly transportation. Residents ought to modify their consumption patterns and endeavor to embrace a low-emission way of living.

The results demonstrate that the scenario prediction results of the residents’ living carbon emissions in Hebei Province show that the residents’ living carbon emissions in Hebei Province have been on the rise under the baseline scenario, and there is no peak; under the low-carbon scenario, it will peak in 2029, with a peak of 174.69 million tons; in the carbon inclusive scenario, it will peak in 2028, with a peak of 173.27 million tons.

Comments 5: The paper has cited some relevant studies, but it seems that these references have not been deeply discussed in combination with the situation in Hebei Province.

Response 5: Thank you for pointing that out. We agree with that comment. Therefore, we have described the actual situation of Hebei Province in the introduction, including its economic development, carbon emission, and population size. The addition in the revised version is on page 2, lines 89-97. Add details as follows:

Since the implementation of the integration of Beijing, Tianjin, and Hebei in 2014, the economy of Hebei Province has developed rapidly, and the total amount of carbon dioxide emissions has been ranked second in the country all year round. The results of the seventh census of Hebei Province in 2020 show that the total population of the province has reached 74.61 million. To effectively reduce carbon emissions and achieve sustainable development, this study focuses on the influencing variables and trend analysis of carbon emissions of inhabitants in Hebei Province. The accomplishment of China's 2030 carbon peak and 2060 carbon neutral aim is very significant from a scientific and practical standpoint.

Comments 6: The paper abstract did not elaborate on the specific calculation results and prediction results of carbon emissions.

Response 6: Thank you for pointing that out. We endorse the recommendation to include specific calculations in the summary. Therefore, we have added the calculated data results and forecast results of this study to the summary. The addition in the revised version is on page 1, lines 18-19 and 27-29. Add details as follows:

The results show that the total carbon emissions of residents in Hebei Province from 2005 to 2020 are rising, from 77.45 million tons to 153.35 million tons.

However, under the low-carbon situation, the carbon emissions of residents in Hebei Province will peak in 2029, with a peak of 174.69 million tons, whereas under the ultra-low-carbon scenario, it will peak in 2028, with a peak of 173.27 million tons.

Comments 7: It is suggested to analyze the differences in the adoption of low-carbon technologies in different regions of Hebei Province and how these differences affect carbon emissions.

Response 7: Thank you for pointing that out. We agree with that comment. However, the collection of low-carbon technologies in different areas of Hebei Province requires a lot of manpower and time investment. Therefore, this is the current limitation of this study, and we will include low-carbon technologies in different regions in the next study. The addition in the revised version is on page 16, lines 477-482. Add details as follows:

3.5. Limitation

In this study, only five factors were selected in the study of the influencing factors of residents’ living carbon emissions. Other factors related to the reduction of residents' living carbon emissions, such as education, policy incentives, and consumer behavior changes, were not analyzed. Therefore, in future work, the factors will be more refined and further discussed.

Comments 8: In the analysis of impact factor, further explore the role of education, policy incentives, and changes in consumer behavior in reducing carbon emissions of residents, except for technological progress.

Response 8: Thank you for pointing that out. We agree with that comment. When selecting image factor analysis, only 5 related factors were selected in this study, so more influencing factors will be added in the next study to explore their impact on carbon emissions. The addition in the revised version is on page 17, lines 527-532. Add details as follows:

In addition, the object of this study is not to distinguish urban and rural residents in Hebei Province as a whole. In future research, it is necessary to be more refined to distinguish urban and rural areas, which can better reveal the differences in carbon emissions caused by individual differences between urban and rural residents, low-carbon technology differences, etc., to more effectively complete the carbon emission reduction targets of Hebei Province.

Comments 9: Moderate editing of English language required.

Response 9: Thanks for your suggestion. We have tried our best to polish the language in the revised manuscript.

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript is well organized and the summary is well supported by the results. Overall, I suggest it can be accepted for publication in this journal current form.

Comments on the Quality of English Language

Minor editing of English language required.