Spatio-Temporal Dynamics and Driving Forces of Multi-Scale Emissions Based on Nighttime Light Data: A Case Study of the Pearl River Delta Urban Agglomeration

Round 1

Reviewer 1 Report

1. Regarding Spatiotemporal sequence forecasting and spatial data interpolation , more recent works should be referenced, such as:
a) Multi-scale urban passenger transportation CO2 emission calculation platform for smart mobility management[J]. Applied Energy, 2023, 331: 120407.
b) Machine learning for spatiotemporal sequence forecasting: A survey. arXiv:1808.06865, 2018
c) Deep spatiotemporal residual early-late fusion network for city region vehicle emission pollution prediction[J]. Neurocomputing, 2019, 355: 183-199.
d) Regional Spatiotemporal Collaborative Prediction Model for Air Quality[J]. IEEE Access, 2019, 7: 134903-134919.
e) Spatiotemporal graph convolution multifusion network for urban vehicle emission prediction[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 32(8): 3342-3354.

2. It is better to present the descriptive statistics of the data for the general overview of the data to avoid extreme data being used in the analysis.

3. In Table 1, what is the meaning of t/t and 104t/104t. Can you calrify them clearly?

4. The notations of CO2t are not unified in Eq.3 and line 177.

5. The subcaptions of Fig.2 need to be adjusted. And there is Chinese text in Fig.3.

6. In Fig.7, what's the meaning of "front of wjG" and "after of wjP".

7. The part of the discussion needs to be added, clarifying the main academic contributions of the manuscript and comparing the differences with existing research results, without shying away from the shortcomings of the manuscript's methodology and possible paths for improvement.

The English Language needs to be improved.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

The article presents a carbon emission estimation model of Pearl River Delta urban agglomeration at the municipality and county levels. This approach utilizes spatial statistics, spatial autocorrelation, spatio-temporal hotspot analysis, and the Theil index to identify differences in urban carbon emission in the mentioned study area. The results show an error in the model of 10.78%. Additionally, the authors discovered that carbon emission levels fluctuated, and the spatial distribution of carbon emissions at municipal and county levels was small. 

The carbon emissions and their spatio-temporal distributions are an interesting research topic. In this sense, the submitted paper is a valuable contribution. However, the article must be prepared for journal publication. The following are my major points of criticism:

 

Introduction

- Introduction needs an in-depth improvement. It is infrequent to see more details about the contribution of this article in the abstract than in the Introduction section. This section must clearly explain the problem, contributions of this approach, and related works.

 

Literature review

- Most of the references utilized are associated with Chinese authors. Only five references do not belong to Chinese authors. Despite the relevance of these works, the authors must include additional works. 

- The relation between urban carbon emissions and nighttime lights must be clearly explained.

- The authors should include the following articles:

• Xia, S., Shao, H., Wang, H., Xian, W., Shao, Q., Yin, Z., & Qi, J. (2022). Spatio-Temporal Dynamics and Driving Forces of Multi-Scale CO2 Emissions by Integrating DMSP-OLS and NPP-VIIRS Data: A Case Study in Beijing-Tianjin-Hebei, China. Remote Sensing, 14(19), 4799.
• Liu, Y., Xia, C., Ou, X., Lv, Y., Ai, X., Pan, R., ... & Zheng, X. (2023). Quantitative structure and spatial pattern optimization of urban green space from the perspective of carbon balance: A case study in Beijing, China. Ecological Indicators, 148, 110034.

 

- There are significant similarities between the author’s approach and some related works (e.g., [6], [19], and the ones mentioned in the previous comment). In this sense, the authors must compare their contribution with these articles, highlighting similarities and differences.

- Limitations of the related work have to be identified in this section.

 

Materials and methods

- Statistical data and administrative boundary data should be characterized. It means including formats and main characteristics of both data sources.

- Concerning regional differences analysis, are results correlated with land use/cover to identify and understand differences?

- “This method hence makes up for the deficiencies of spatial analysis of carbon emissions under grade differences and different weights.” Although this assertion includes two references, it needs more details to understand the process performed.

 

Results

- Introduction to this section needs to improve. Additionally, This section needs an important re-organization since sometimes it takes time to identify an order. For instance, the section starts with some evaluation results and does not present the obtained results.

- Section 4.1 considers two different times (1997-1999 and 2000.2007, 2014, and 2020). Why were these periods considered?

- The authors asserted that the error was less than 10.78%. Which was the exact error value? How was this error distributed in different cities? And counties?

- “The DN value of night light and carbon emission of these cities were divided by 4. Why?

- Section 4.2 -- According to 2.4… This subsection does not appear in the article.

- How and why was temporal distribution set in Figure 3? Different elements of Figure 3 (a, b, c, and d) are not mentioned in section 4.2.

- Variables in Table 2 should be defined.

- “999 random substitutions were carried out”. What is it mean?

- What is the relation of considered data in subsection 4.3.1 with DMSP-OLS and NPP/VIIRS data? Which is the relation of these results with yearbooks?

- Similarities and differences between Figure 4 and Figure 5 should be identified and explained at city and county levels. Also, they have to be shown to local outliers.

- Subsection 4.3.2 mentions a spatio-temporal cube. How was it developed?

- What were the criteria for defining diverse categories of Figure 6? How were the size of grids defined?

- Subsections 4.3.2 and 4.3.3 have the same title.

- Several variables and indicators appear in subsection 4.3.3 but are not defined.

- “The contribution within cities was greater than that between cities, and less than that between cities from 2014 to 2020.” It is confusing. The authors need to clarify it.

- Table 3 and Table 4 contain no data for Dongguan and Zhongshan. Why? Are these values affecting the obtained results?

- The authors asserted that “the development of spatial regions was unbalanced.” What is it mean? What are the consequences?

- “According to 4.7…”. However, this subsection does not appear in the article.

- Figure 7 is not mentioned in the article.

- Section 4.4 mentioned a variable called “the number of enterprises”. However, only the number is a poor variable. The authors must characterize the types of enterprises to identify which industries present more carbon emissions and where they are located.

- Is the carbon emission estimation model a general approach for urban areas in and outside China? Or is this approach specific to the study area?

 

Discussion

- This text may be included in the conclusion section.

 

Other aspects to consider:

The authors should check in references to sections and figures in the article in an exhaustive way. 

The authors must check the titles of sections and the number of sections.

Multiple digitation errors appear in the article. Next, some of them:

-        Which hads been

-        Spac-time

-        There wasis

-        Itthese

-        wasis

Several typos appear in the article and an extensive review of the English language is required.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

I would like to thank authors for very interesting study. I read it carefully and i think that it could be interesting to the readers of the Sustainability journal. It deals with the assessment of carbon emissions on the base of night lights data.

From my point of view, this manuscript requires only minor modification to improve its readability and attractiveness to the readers:

1. It is necessary to decipher all acronyms at the first mention.

2. Sections 3.6.2 and 3.7 require additional details. Methodology should be described step by step to be reproducible.

3. Section 4. I propose to remove the first paragraph. It is meaningless.

4. Equation 3. 0.013 DN?

5. Figure 2. I propose to divide it in separate figures, because the map is too small.

6. I don't see the reason to make a discussion section. You can place these ideas in section 5.

7. Conclusion. I propose to add ideas, what are the reasons for a relatively big error.

Author Response

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Author Response File: Author Response.pdf

Reviewer 4 Report

Dear Authors

The topic of the manuscript “Spatio temporal variation of urban multi-scale carbon emissions and its influencing factors based on night light data: A case study of Pearl River Delta urban agglomeration” in my opinion might be interesting for readers of Sustainability, but manuscript contains many mental shortcuts that must be explained in the article.

I have no hesitation to recommend this manuscript for major revision.

Below I have included a few comments to help the Authors improve their article.

Title

The title in my opinion is too long, too accurate and does not fully correspond to the content of the article. Night data are too little exposed in the article (especially in part of the results). The authors focused mainly on forecasting carbon emissions.

Keywords:  
Authors should delete or replace the keyword that are also in the title of the work. Keywords cannot duplicate parts of the title.

Introduction:

First, the authors should add something about the history of obtaining information about night light data:

The history of Nighttime Light map can trace back early 90, with the Operational Linescan Sensor (OLS) onboard Defense Meteorological Satellite Program (DMSP) satellites. Since the launch of the latest generation of earth observation satellite, the Joint Polar-orbiting Satellite System (JPSS), the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB) on board of JPSS satellites provides astounding improvement on low light imaging compared to DMSP-OLS. Today we are able to use the global Nighttime Light data with superior quality.

Lines 88 and 93 - explain the abbreviation before using it... (even if it's obvious)

From line: 96 - new paragraph (maybe a new chapter: Aim and scope)

The novelty is basically obvious, but research hypotheses should be added

 

Methodology part:

What program was used to calculate: the global Moran's I index and local Moran's I index - this information should be included in the methodology

What GIS program was used to image the results? ArciGIS? – what version, specify the manufacturer

Results

Fig. 3 - unnecessary characters when indicating years. Why is one of the values 0 - was there no data there? Two elements have a clipped area.

 

Line 368 - LISA cluster map - describe in methodology (why this analysis is performed)

 

Discussion

Short, weak and not at all relevant to the title of the article. In the discussion, you should refer to the use of nighttime light data in other studies. 

Numerous typos and punctuation errors were found in the article. The use of English requires corrections.

 

Dear Editor 

The topic of the manuscript “Spatio temporal variation of urban multi-scale carbon emissions and its influencing factors based on night light data: A case study of Pearl River Delta urban agglomeration” in my opinion might be interesting for readers of Sustainability, but manuscript contains many mental shortcuts that must be explained in the article.

I have no hesitation to recommend this manuscript for major revision.

I have included a few comments to help the Authors improve their article.

Author Response

Please see the attachment

 

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Fig.2 need to be adjusted. And there is Chinese text in Fig.2.

Fig.2 need to be adjusted. And there is Chinese text in Fig.2.

Author Response

Thank you very much for providing these reference materials. We have removed the Chinese text in Figure 2.

 

Reviewer 2 Report

The authors performed most of my previous comments in the new version of their article, generating a good contribution. Considering the current version, I recommend publishing this article in the journal.

Author Response

非常感谢您对我们研究的积极反馈和建议。我们将继续努力进行高质量的研究，并期待在期刊上发表文章。

Thank you very much for your positive feedback and suggestions on our research. We will continue to strive for high-quality research and look forward to publishing articles in journals.

Reviewer 4 Report

Dear Authors

 

Thank you for correcting the article according to my suggestions. However, this manuscript should be improved in my opinion in two places:

1. Remove abbreviations from keywords

2. separate discussion from conclusions. Conclusions should be given at the end of the work.

Author Response

Please see the attachment. 

Author Response File: Author Response.pdf