Valuing Carbon Assets for Sustainability: A Dual-Approach Assessment of China’s Certified Emission Reductions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript, “Dual Value Assessment of New Carbon Asset CCER”, assessed China Certified Emission Reduction carbon assets from multiple perspectives, employing the theoretical frameworks of the income approach and market approach. However, there are arguments lack of references and proper analysis. The article’s language also needs significant polish and improvement.  I don’t recommend Sustainability to accept and publish this article. The comments are as follow:

1. Table 1: no reference information.
2. Throughout the article: it appears that the authors used LaTex/MathType textbook style like typesetting software which make it very hard for reviewers to understand. The displaying format can be improved.
3. Line 197, section 3.2.1 first sentence: lack of reference
4. Line 246: a RMSE value rather than an RMSE value
5. Figure 3: lack of proper analysis. The predicted value of October 2023 undermines the accuracy of the model, there are large discrepancy between real value and predicted value.
6. Line 249: The number of iterations is determined to be 1200. This needs more explanation. Figure 4 doesn’t plot the iteration till 1200. If the RMSE level has come to a stable level, why not choose a smaller number of iterations?
7. Line 307 to 309: redundant calculation process is unnecessary.
8. Line 309, equation result shows 3110.35 without any unit while line 311 claims the practical value is 31.1035 million. This contradiction needs to be interpreted.
9. Line 357: and sets the prediction results to “what”? All I can see are commas and periods.

 

Comments on the Quality of English Language

In Section 4.2 (3)Determination of volatility – σ. This is a poorly written paragraph. And this type of expression has appeared more than once in the article. The verb such as select, calculate and take without any host mentioned leading the paragraph hard to follow. You can write it this way:

The daily transaction price data from the national carbon trading market from 2021 to 2023 was selected. After removing non-trading days, the ratio of each trading day's price to the previous day's price was calculated and the natural logarithm of these ratios were produced.

The whole articles language needs to be polished.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Overall, the document effectively describes and contextualizes its content in relation to existing theory and research. The literature review is thorough, and the methodological decisions are well justified.

Comments for author File: Comments.pdf

Author Response

  We feel really grateful for the reviewer’s suggestions and commends. Some perspectives have greatly enriched and deepened my academic understanding in the topic and area. It benefits us more than this paper itself. Besides answering all the questions, we have greatly improved this article.

  We have incorporated additional literature pertaining to CCER to augment the scholarly rigor of the article. Following the acquisition of the research results, we also conducted a validation of the model's accuracy, with the intention of rendering the research findings more persuasive. This information is detailed in Chapter 4.4.

Reviewer 3 Report

Comments and Suggestions for Authors

Reviewer comments:

This study proposes an integrated value assessment model for CCER that combines Long Short-Term Memory (LSTM) neural network-based carbon price forecasting with both the discounted net cash flow method and the Black-Scholes option pricing framework, applying this model to a wind power project. The data is valuable and the results are interesting. However, there are some problems for this manuscript. The main problems are 1) the section of Literature review and Assessment of the market value of CCER could be improved, and 2) the format of this study is not standardized. I think that at this stage, the article could be improved until an revised version was provided.

Detailed comments:
1) 2. Literature review: Based on the content of the case analysis below, in the literature review, should the influencing factors of carbon trading prices be supplemented, such as energy production and electricity consumption factors?

2) 3. Practical value assessment of CCER: Does the data in Figure 5 have no units?

3) 3. Practical value assessment of CCER: Is the last sentence of the first paragraph in 3.3 missing any words ? For example, The detailed calculation methodology and outcomes are presented in?

4) 4. Assessment of the market value of CCER: In the formulas (2), (3) and (4), what do the parameters N(d1), N(d2), d1 and d2 refer to?

5) 4. Assessment of the market value of CCER：Is the last sentence of the first paragraph in 4.1 and the first paragraph in 4.3 missing any words ? For example, the applicability of this model is predicated on several foundational assumptions, as illustrated in? ... in each period, as shown in ? and ?, and then substituting into formula (2) to obtain the option value of 𝐶1~𝐶10, as shown in ? below.

6) 4. Assessment of the market value of CCER：Whether the assessment results should be examined ?

7) References: There are repetitions in the references, such as “Li Y, Song J. Research on the Application of GA-ELM Model in Carbon Trading Price – An Example of Beijing. Pol J Environ Stud 2021;31:149–61. https://doi.org/10.15244/pjoes/138357.” appearing twice.

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

Title: Valuing Carbon Assets for Sustainability: A Dual-Approach Assessment of China’s Certified Emission Reductions
by Jiawen Liu, Yue Liu, Jiayi Wang , Xinyue Chen , Liyuan Deng
This work studies an integrated value assessment model for CCER that combines Long Short-Term
Memory neural network-based carbon price forecasting with both the discounted net cash flow method
and the Black-Scholes option pricing framework. The study finds that the practical value of CCERs,
derived from verified emission reductions, significantly exceeds their market option value, underscoring
the economic and environmental viability of such projects. By distinguishing between the realized and
potential values of carbon credits, this work offers a comprehensive tool for carbon asset valuation that
supports corporate carbon management and policy development. The frame work contributes to the
growing literature on sustainable finance by aligning carbon asset pricing with long-term climate goals
and enhancing transparency in carbon markets.
I can recommend the paper for publication. But the author should check the misprints
(especially for references and citations) and correct them.
Minor comments
1. The following papers are related to this work, so please add them in the References. (i)Gu C.
Research on Prediction of Investment Funds Performance before and after Investment Based on
Improved Neural Network Algorithm. Wireless Communications and Mobile Computing, 2021(1).
https://doi.org/10.1155/2021/5519213.
(ii) Zhong W , Yue W , Haoran W ,et al.Integrating fast iterative filtering and ensemble neural
network structure with attention mechanism for carbon price forecasting. Complex & Intelligent
Systems, 2025, 11(1).DOI:10.1007/s40747-024-01609-7.

Comments for author File: Comments.pdf

Author Response

  We feel really grateful for the reviewer’s suggestions and commends. Some perspectives have greatly enriched and deepened my academic understanding in the topic and area. It benefits us more than this paper itself. Besides answering all the questions, we have greatly improved this article.

  Thank you very much for your suggestions. I have added the references you recommended, which you can find in line 285 and line 174. I also appreciate your reminder; we have corrected the references and the errors that occurred in the article due to format conversion.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

All the revisions that are needed are properly addressed by the authors, no more comments or suggestions.