Carbon Pressure and Economic Growth in the Urban Agglomeration in the Middle Reaches of the Yangtze River: A Study on Decoupling Effect and Driving Factors

Round 1

Reviewer 1 Report

Dear Authors , Thank you for your paper.

I have following major comment:

1-    The Authors need to changed future tens for the period from 2015 to 2020 to past tense, specifically in the following:

a.      From 2000 to 2020, the carbon pressure of the majority of cities will increase,

b.     The amount of carbon pressure has been growing from 2000-2015 and will be slightly lower in 2020 than in 2015, while the carrying capacity has remained unchanged and will be somewhat lower in 2020.

c.     In 2020, the carbon pressure of Wuhan urban agglomeration, the urban agglomeration encircling Poyang Lake and the urban agglomeration around Changsha-Zhuzhou-Xiangtan will be 3.14, 2.18 and 1.49 respectively, with the increase of 35%, 281% and 205% respectively compared with 2000.Wuhan urban agglomeration has the highest carbon pressure and the lowest average annual growth rate.

d.     Yangtze River will be energy consumption, followed by economic growth,

e.     In contrast, urban agglomeration encircling Poyang Lake and urban agglomeration around Changsha-Zhuzhou-Xiangtan have a lower carbon pressure level; however, the increase is greater. They will face a greater carbon increment pressure in the future.

2-    Please confirm the number of cities that were covered in the study. In the paper, it is mentioned as 31 cities, but in some places, it is mentioned as 13 cities.

3-    The authors need to correct the phrase "et al." to "and other factors" or "and so on" in the section where they mention "sure and natural factors, social factors, et al."

4-    Please make the text all the figure clearer

5-    Finally, I have a major concern with the conclusion, hence it already known that energy consumption and economic growth are major causes of the climate change.  

Author Response

please see theattachment

Author Response File: Author Response.pdf

Reviewer 2 Report

The introduction briefly presents the context in which this work is located, followed by a detailed and rich list of previous studies in which the concepts underlying the research are defined.

The description of the research methodology is understandable as it shows the mathematical formulas used and the specifications of the individual elements present in them.

Overall, the study appears well structured and very interesting, offering an important contribution to understanding the relationship between carbon pressure and economic growth, its evolution and the various factors that interact.

The results are clear as well as the scenarios for new and more in-depth research.

English is well written and easily understood.

Publication in the current version is recommended.

Author Response

We are very grateful to Reviewer for reviewing the paper so carefully.Thank you for your support and affirmation

Reviewer 3 Report

The work is good and it can be improved by adding these suggestion:

1- The figures 2, 3, 5,and  6 is not visible. redraw good quality figures.

2- the carbon pressure data is presented but it is not mentioned any solution/ technique to reduce it in future?

3-Some natural methods to control carbon e.g plantation or other treatment will be useful or not? describe pros and cons in policy suggestion,.

4- Is there any mitigation techniques to reduce carbon pressure keeping population and energy on growth side to make environment sustainable?

Author Response

Dear Reviewer:

We sincerely thank the editor and all reviewers for your valuable feedback that we have used to improve the quality of our manuscript. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes to the manuscript are given in the red text.

Comment 1. The figures 2, 3, 5,and 6 is not visible. redraw good quality figures.

We appreciate your feedback. We have modified the font in the figure to make it clearer and easier to read.

Comment 2. the carbon pressure data is presented but it is not mentioned any solution/ technique to reduce it in future?

Thank you for pointing out this point. We have revised it accordingly as following (line524-535, clean version of manuscript): Present regional disparities in carbon pressure in the middle reaches of the Yangtze River urban agglomeration are primarily attributable to energy consumption and economic expansion. Energy consumption is the most influential in reducing overall carbon pressure, as it inhibits the increase. The economic intensity impact is the most significant factor contributing to the rise in carbon pressure. Secondly, the government should change the industrial structure to lower the secondary industry's large proportion of energy consumption in the middle reaches of the Yangtze River urban agglomeration. Second, the government can reduce its use of traditional fossil fuels and in-crease its investment in scientific and technological research and development to im-prove energy efficiency. Thirdly, the government can lessen economic growth's reliance on high-carbon industries by fostering the fast development of the tertiary industry and emphasizing the pull of high-tech industries on economic development.

Comment 3. Some natural methods to control carbon e.g plantation or other treatment will be useful or not? describe pros and cons in policy suggestion.

Thank you for pointing out this point. We have revised it accordingly as following (line536-542, clean version of manuscript): At the same time, the government can also strengthen the protection and restoration of the ecosystem in the middle reaches of the Yangtze River urban agglomeration to improve the carbon absorption capacity of the urban agglomeration, thus effectively reducing carbon pressure. Local governments can improve the carbon adsorption capacity of regional ecological nature by adjusting the forest planting structure and in-creasing the forest stock. Each urban cluster should protect grasslands and wetlands, expand woodlands, and develop unused land to increase carbon storage and reduce emissions.

Comment 4. Is there any mitigation techniques to reduce carbon pressure keeping population and energy on growth side to make environment sustainable?

Thank you for pointing out this point. We have revised it accordingly as following (line543-545, clean version of manuscript): the government should also vigorously promote the development of carbon capture, CCS, and utilization and sequestration technologies to provide technical support for reducing carbon pressure.

Author Response File: Author Response.pdf

Reviewer 4 Report

The manuscript gives an account on carbon pressure and economic growth in the urban agglomeration in the middle reaches of the Yangtze River. The manuscript is nicely written, clear and concise. The paper employs a good design and a well-consolidated methodology. Authors restrain from too much theorizing.

Minor revisions:

Check the consistence of references cited in the table 1

In my opinion in Reseach area paragraph, it would be advisable to add a table summarizing the following information for each city: geographical location (coordinates), number of inhabitants and population density relating to 2000 and 2020

If possible, the authors should clarify whether the pandemic event influenced the 2020 trend, pointed out at pages 7 and 8. 

Author Response

Dear Reviewer:

We sincerely thank the editor and all reviewers for your valuable feedback that we have used to improve the quality of our manuscript. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes to the manuscript are given in the red text. 

Comment 1. Check the consistence of references cited in the table 1

Thank you for pointing out this point. We have reworked the references in Table 1

Land use type		Carbon Sink Factor	Reference Sources
Woodland	With woodland	0.87	Fang et al.[38].、Tang et al.[39].
	Shrubland	0.23
	Open woodland	0.58
	Other woodland	0.2327
Grassland	High cover grassland	0.138	Piao et al. [40]、 Fang et al. [36].
	Medium cover grassland	0.046
	Low-cover grassland	0.021
Water area	River and canal	0.671	Kong et al. [41]
	Lakes	0.303
	Reservoir ponds	0.303
	Mudflats	0.567
	Beachland	0.567
Unused land	Unused land	0.0005	Li et al. [42].

36. Fang, J.; Guo, Z.; Piao, S.; Chen, A. Terrestrial vegetation carbon sinks in China, 1981–2000. Science in China Series D: Earth Sciences2007, 50, 1341-1350. [Google Scholar] [CrossRef]
37. Zhang, H.; Peng, Q.; Wang, R.; Qiang, W.; Zhang, J. Spatiotemporal patterns and factors influencing county carbon sinks in China. Acta Ecol. Sin 2020,40, 8988-8998. [Google Scholar] [CrossRef]
38. Fang, J.; Yu, G.; Liu, L.; Hu, S.; Chapin III, F. S. Climate change, human impacts, and carbon sequestration in China. Proceedings of the National Academy of Sciences2018, 115, 4015-4020. [Google Scholar]
39. Tang, X.; Zhao, X.; Bai, Y.; Tang, Z.; Wang, W.; Zhao, Y.; et al. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey.Proceedings of the National Academy of Sciencesn2018, 115, 4021-4026. [Google Scholar] [CrossRef]
40. Piao, S.; Fang, J.; Zhou, L.; Zhu, B.; Tan, K.; Tao, S. Changes in vegetation net primary productivity from 1982 to 1999 in China.   

Global Biogeochemical Cycles 2005, 19, 8988-8998. [Google Scholar] [CrossRef]

41. Kong, D. S.; Zhang, H. Economic value of wetland ecosystem services in the Heihe National Nature Reserve of Zhangye. Acta Ecologica Sinica2015, 35, 972-983. [Google Scholar]
42. Lai, L.; Huang, X. J.; Liu, W. L. Adjustment for regional ecological footprint based on input-output technique: A case study of Jiangsu Province in 2002. Acta Ecologica Sinica2006, 26, 1285-1292. [Google Scholar]

Comment 2. In my opinion in Reseach area paragraph, it would be advisable to add a table summarizing the following information for each city: geographical location (coordinates), number of inhabitants and population density relating to 2000 and 2020.

We agree that the table you mentioned would be helpful in understanding the details, and after careful evaluation, we believe that additional factors such as economic factors would be needed to enrich the details. However, we find that this table would take up too much space and therefore we are unable to include it in the text. However, we believe that the current presentation will still help the reader to understand the Yangtze River Central Urban Agglomeration, and we have included a table for you to understand it better.

City	geographical location	Year	Permanent Population (10,000 people)	Population Density (people/km²)
Nanchang	28.68202°N, 115.85794°E	2000	250.70	793
		2020	563.10	1196
Jingdezhen	29.26869°N, 117.17839°E	2000	44.20	451
		2020	42.50	443
Pingxiang	27.62289°N, 113.85427°E	2000	42.20	344
		2020	47.10	406
Jiujiang	29.70548°N, 116.00193°E	2000	139.20	358
		2020	58.50	442
Xinyu	27.81776°N, 114.91713°E	2000	27.70	355
		2020	28.10	374
Yingtan	28.26019°N, 117.06919°E	2000	36.70	439
		2020	31.50	484
Ji'an	27.11382°N, 114.99376°E	2000	40.00	201
		2020	40.20	243
Yichun	27.81443°N, 114.41612°E	2000	52.50	236
		2020	53.50	280
Fuzhou	27.94781°N, 116.35809°E	2000	37.90	170
		2020	37.50	203
Shangrao	28.45463°N, 117.94357°E	2000	72.10	244
		2020	71.20	274
Wuhan	30.59276°N, 114.30525°E	2000	753.00	1138
		2020	1110.90	1497
Huangshi	30.19953°N, 115.03890°E	2000	71.80	422
		2020	68.50	408
Yichang	30.69186°N, 111.28647°E	2000	68.20	184
		2020	68.50	244
Xiangyang	32.00900°N, 112.12255°E	2000	66.20	392
		2020	66.80	405
Ezhou	30.39085°N, 114.89495°E	2000	31.90	738
		2020	34.50	758
Jingmen	31.03546°N, 112.19945°E	2000	60.50	415
		2020	57.90	404
Xiaogan	30.92483°N, 113.91645°E	2000	66.20	375
		2020	66.50	407
Jingzhou	30.33517°N, 112.23974°E	2000	83.60	270
		2020	84.60	295
Huanggang	30.45347°N, 114.87238°E	2000	72.90	266
		2020	69.30	268
Xianning	29.84126°N, 114.32245°E	2000	67.70	306
		2020	63.40	320
Xiantao	30.36251°N, 113.45450°E	2000	43.70	253
		2020	76.50	476
Qianjiang	30.40147°N, 112.89930°E	2000	49.20	444
		2020	66.00	573
Tianmen	30.66339°N, 113.16614°E	2000	48.20	380
		2020	79.70	589
Changsha	28.22821°N, 112.93881°E	2000	652.20	763
		2020	840.30	1226
Zhuzhou	27.82767°N, 113.13396°E	2000	382.00	694
		2020	352.00	945
Xiangtan	27.82975°N, 112.94411°E	2000	246.00	677
		2020	303.10	1070
Hengyang	26.89368°N, 112.57195°E	2000	713.00	497
		2020	727.70	780
Yueyang	29.35728°N, 113.12896°E	2000	515.40	408
		2020	542.50	540
Changde	29.03158°N, 111.69854°E	2000	554.90	285
		2020	610.00	465
Yiyang	28.55386°N, 112.35516°E	2000	230.60	422
		2020	277.70	638
Loudi	27.69728°N, 112.00108°E	2000	122.60	204
		2020	124.30	284

 

Comment 3. If possible, the authors should clarify whether the pandemic event influenced the 2020 trend, pointed out at pages 7 and 8.

Thank you for pointing out this point. We have revised it accordingly as following (line258-259, clean version of manuscript): At the same time, carbon emissions are reduced due to the impact of the New Crown Pneumonia outbreak, resulting in a significant reduction in carbon pressure in 2020. (reference: Peng, Z.M, Wu, H.H. Energy consumption, eco-environmental pollution and industrial restructuring and upgrading in Yangtze river economic belt. Resources and Environment in the Yangtze Basin,2022,31,1694-1704. )

Author Response File: Author Response.pdf

Reviewer 5 Report

The authors investigated the changes in carbon pressure on cities within the urban agglomeration in the middle reaches of the Yangtze River, China. Carbon pressure was defined as the ratio of carbon emissions to carbon carrying capacity (i.e., carbon sinks). Using a decomposition model, they determined that the carbon pressure experienced between 2000 and 2020 was mainly affected by energy consumption and economic growth. The authors also provided some recommendations to local authorities on reducing carbon pressure within the region.

Overall, the paper is well written with few editing and grammatical errors. I recommend a major revision of this manuscript with the possibility of acceptance after the following have been included in the manuscript:

·       The 5-year time step implemented in this analysis is of a very low resolution relative to the 20-year time range. Although the authors mention some data limitations, they should have implemented higher spatial resolution analyses on select cities in each province or particularly interesting cases where there were undulating trends in the carbon pressure (e.g., Yingtan). The authors should include these cases for better discussions on the trends and observations, within the limits of data availability.

·       The perceived drop in the 2020 values should not only be cursorily ascribed to a 2012 policy. Were there other regional factors that induced this? Could this be due to the COVID-19 pandemic that severely dampened industrial and economic activities within this region and the rest of the world? The authors need to either provide higher-resolution data to back this up and/or discuss the effects of COVID-19 and other factors on the carbon pressure trend.

·       It is interesting that the carbon carrying capacities of the cities that are shown in Figure 2 and described in the text remained mostly unchanged during the 20-year period. Can the authors explain why this is so? I would think that the effect of extensive urbanization and industrialization in these areas could have induced some land use change and impacted (reduced the area of) the available carbon sinks. Can the authors please provide some clarity on the carbon carrying capacity dataset?

·       Also, please correct the following:

o   Some abbreviations are not defined e.g., DMSP/OLS, IPAT, IPCC, etc. Even though these may be common abbreviations in the authors’ fields of study, they should be defined in the text.

o   Figure 1 is not referenced in the main text. Kindly include it in the text. Also, the caption does not explain the figure. What does DEM in the color bar mean?

o   In your decomposition model, you define “energy structure” as the ratio of the carbon pressure to energy consumption. Is this the same as the “energy mix” in the plots in Figures 5 and 6? If so, please use the same term. I recommend you stick with “energy structure”.

 

o   Fix the citation in Table 1. 

Author Response

We sincerely thank the editor and all reviewers for your valuable feedback that we have used to improve the quality of our manuscript. The reviewer comments are laid out below in italicized font and specific concerns have been numbered. Our response is given in normal font and changes to the manuscript are given in the red text:

Comment 1. The 5-year time step implemented in this analysis is of a very low resolution relative to the 20-year time range. Although the authors mention some data limitations, they should have implemented higher spatial resolution analyses on select cities in each province or particularly interesting cases where there were undulating trends in the carbon pressure (e.g., Yingtan). The authors should include these cases for better discussions on the trends and observations, within the limits of data availability.

We agree that additional research would be helpful to understand the details, and after carefully assessing the conditions required to complete these additions, we found that we were unable to find the appropriate data to carry out this work. We believe the present results can still support the conclusion of this paper. Therefore, we suggest that supplementary experiments be included in future papers.

Comment 2. The perceived drop in the 2020 values should not only be cursorily ascribed to a 2012 policy. Were there other regional factors that induced this? Could this be due to the COVID-19 pandemic that severely dampened industrial and economic activities within this region and the rest of the world? The authors need to either provide higher-resolution data to back this up and/or discuss the effects of COVID-19 and other factors on the carbon pressure trend.

Thank you for pointing out this point. We have revised it accordingly as following (line258-259, clean version of manuscript): At the same time, carbon emissions are reduced due to the impact of the New Crown Pneumonia outbreak, resulting in a significant reduction in carbon pressure in 2020. (reference: Peng, Z.M, Wu, H.H. Energy consumption, eco-environmental pollution and industrial restructuring and upgrading in Yangtze river economic belt. Resources and Environment in the Yangtze Basin,2022,31,1694-1704. )

Comment 2.It is interesting that the carbon carrying capacities of the cities that are shown in Figure 2 and described in the text remained mostly unchanged during the 20-year period. Can the authors explain why this is so? I would think that the effect of extensive urbanization and industrialization in these areas could have induced some land use change and impacted (reduced the area of) the available carbon sinks. Can the authors please provide some clarity on the carbon carrying capacity dataset?

Thanks for your question. The land use data used for the carbon carrying capacity were obtained from the Resource and Environmental Science Data Center of the Chinese Academy of Sciences (https://resdc.cn/), using five phases of Landsat remote sensing images from 2000, 2005, 2010, 2015 and 2020 as the main data source, with an accuracy of 30m 30m. These data were obtained by manual visual interpretation. In fact, there is a change in land use, and the calculated carbon carrying capacity decreases year by year, but the decrease is not much, and the carbon carrying capacity basically remains stable. The specific data are shown in the following table.

Urban ag-glomeration	Year	Carbon Carrying Capacity
Urban agglomeration encircleing Poyang Lake	2000	11617.46277
	2005	11596.87271
	2010	11751.54545
	2015	11676.94525
	2020	11631.35564
Wuhan urban agglomeration	2000	7097.740829
	2005	7145.580588
	2010	7220.327686
	2015	7197.96871
	2020	7102.602886
Urban agglomeration around Changsha-Zhuzhou-Xiangtan	2000	8483.820148
	2005	8470.188302
	2010	8388.138851
	2015	8310.909598
	2020	8265.118669
Urban agglomeration in the middle reaches of the Yangtze River	2000	27199.02374
	2005	27212.6416
	2010	27360.01199
	2015	27185.82356
	2020	26999.07719

 

Comment 3. Also, please correct the following:

o  Some abbreviations are not defined e.g., DMSP/OLS, IPAT, IPCC, etc. Even though these may be common abbreviations in the authors’ fields of study, they should be defined in the text.

Thank you for pointing out this point. We have revised it accordingly as following (line61-67, clean version of manuscript): The two most popular approaches for measuring carbon emissions are the Independent Police Complaints Commission (IPCC)'s reference method and the Defense Meteorological Satellite Program/ Operational Linescan System(DMSP/OLS) nighttime lighting data method [22] [23]. The IPCC technique is the simplest, most straightforward, and easiest to comprehend. It has a mature accounting formula and activity data [24], making it the method of choice for many academics.

(line76-80, clean version of manuscript): Kang (2012) [29] utilized the IPAT equation which is a quantitative relational model that represents the impact of human activities on the environment and log-averaged Divisia index de-composition model (LMDI technique) to refine the elements impacting the decoupling relationship between carbon emissions and economic development.

o   Figure 1 is not referenced in the main text. Kindly include it in the text. Also, the caption does not explain the figure. What does DEM in the color bar mean?

Thank you for pointing out this point. We have revised it accordingly as following (line110-119, clean version of manuscript): According to the "Development Plan of the urban agglomeration in the middle reaches of the Yangtze River" approved by the Chinese government in 2015, the scope of the urban agglomeration in the middle reaches of the Yangtze River covers 13 cities in Hubei Province, including Wuhan, Huangshi, Ezhou, Huanggang, Xiaogan, Xianning, Xiantao, Qianjiang, Tianmen, Xiangyang, Yichang, Jingzhou and Jingmen; 8 cities in Hunan Province, including Changsha, Zhuzhou, Xiangtan, Yueyang, Yiyang, Changde, Hengyang, and Loudi; and 10 cities in Jiangxi Province, including Nanchang, Jiujiang, Jingdezhen, Yingtan, Xinyu, Yichun, Pingxiang, Shangrao, Fuzhou, and Ji'an (Figure 1).

We have explained the figure 1 accordingly as following: Geographical location of the urban agglomeration in the middle reaches of the Yangtze River. The DEM in the figure is a digital elevation model, which is a discrete mathematical representation of the topography of the earth's surface

o   In your decomposition model, you define “energy structure” as the ratio of the carbon pressure to energy consumption. Is this the same as the “energy mix” in the plots in Figures 5 and 6? If so, please use the same term. I recommend you stick with “energy structure”.

Thank you for pointing out this point. We have changed the text in Figure 5 and Figure 6

 

 

o   Fix the citation in Table 1.

Thank you for pointing out this point. We have reworked the references in Table 1

Land use type		Carbon Sink Factor	Reference Sources
Woodland	With woodland	0.87	Fang et al.[38].、Tang et al.[39].
	Shrubland	0.23
	Open woodland	0.58
	Other woodland	0.2327
Grassland	High cover grassland	0.138	Piao et al. [40]、 Fang et al. [36].
	Medium cover grassland	0.046
	Low-cover grassland	0.021
Water area	River and canal	0.671	Kong et al. [41]
	Lakes	0.303
	Reservoir ponds	0.303
	Mudflats	0.567
	Beachland	0.567
Unused land	Unused land	0.0005	Li et al. [42].

36. Fang, J.; Guo, Z.; Piao, S.; Chen, A. Terrestrial vegetation carbon sinks in China, 1981–2000. Science in China Series D: Earth Sciences 2007, 50, 1341-1350. [Google Scholar] [CrossRef]
37. Zhang, H.; Peng, Q.; Wang, R.; Qiang, W.; Zhang, J. Spatiotemporal patterns and factors influencing county carbon sinks in China. Acta Ecol. Sin 2020, 40, 8988-8998. [Google Scholar] [CrossRef]
38. Fang, J.; Yu, G.; Liu, L.; Hu, S.; Chapin III, F. S. Climate change, human impacts, and carbon sequestration in China. Proceedings of the National Academy of Sciences 2018, 115, 4015-4020. [Google Scholar]
39. Tang, X.; Zhao, X.; Bai, Y.; Tang, Z.; Wang, W.; Zhao, Y.; et al. Carbon pools in China’s terrestrial ecosystems: New estimates based on an intensive field survey.Proceedings of the National Academy of Sciencesn 2018, 115, 4021-4026. [Google Scholar] [CrossRef]
40. Piao, S.; Fang, J.; Zhou, L.; Zhu, B.; Tan, K.; Tao, S. Changes in vegetation net primary productivity from 1982 to 1999 in China.

Global Biogeochemical Cycles 2005, 19, 8988-8998. [Google Scholar] [CrossRef]      

41. Kong, D. S.; Zhang, H. Economic value of wetland ecosystem services in the Heihe National Nature Reserve of Zhangye. Acta Ecologica Sinica 2015, 35, 972-983. [Google Scholar]
42. Lai, L.; Huang, X. J.; Liu, W. L. Adjustment for regional ecological footprint based on input-output technique: A case study of Jiangsu Province in 2002. Acta Ecologica Sinica 2006, 26, 1285-1292. [Google Scholar]

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Dear Authors, Thank you for your response. I think the paper can be accepted. I appreciate your effort and dedication in revising your manuscript based on our feedback. 

Good luck!

 

Reviewer 5 Report

My comments have been adequately addressed. I now recommend acceptance in the current form.