Forecast of Transportation CO2 Emissions in Shanghai under Multiple Scenarios
Round 1
Reviewer 1 Report
1. This manuscript is written well in English. However, today is 2022 but why the data was only updated until 2019? Because it was written in 2019 and then submitted for review until now? Also in the conclusion it said “we forecast … 2021 to 2035”, again, it’s 2022 already so please modify the description accordingly.
2. If you have 2020 and 2021’s data, is that able to compare the model prediction and the real number?
3. I agree the new energy car is still a small portion so that it cannot affect the total CO2 emission significantly right now. However, due to its rapid growth rate and government policy support, several years late I do believe EV cars will occupy a big portion in China. Looks like right now EV cars made up almost a quarter of all new passenger car sold in China so I think it’s important to consider the impact of EV cars in the prediction mode. Maybe the author can add a separated paragraph showing the estimated amount of new energy cars in the next several years and then how much it will affect CO2 emission accordingly.
4. There are too much general concept in the conclusion, lack of solid number to support the claim. For example, in conclusion you talk about the government should support new energy cars, yes, we all know that, but how much it will help? We need some numbers to give an idea what goals should be achieved. If your analysis shows that by 2030 Shang Hai EV cars can reach 30% of the total cars, it will help low 40% CO2 emission, something like this. Otherwise we can’t get any solid benefits from the model and your comments about the government should actively promote green and low-carbon travel is not that persuasive.
5. The authors need to show how to use the model to support government discussion making process.
6. The authors need to emphasize the advantage of your extended STIRPAT model compared to LMDI method, regression method, and STIRFDT model. If the other’s model is better they just simply need to update the database.
7. Line 437, “finds” should be “found” with past tense.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
1. The novelty and originality shall be justified that the manuscript contains sufficient contributions to the new body of knowledge from the international perspective in addition to focusing on the issues of one country/region. The knowledge gap needs to be clearly addressed.
2. Literature review is insufficient to present the most updated status for further justification of the originality of the manuscript. The authors should carry out a thorough literature review of papers published in a range of top energy and resource journals in the last three/four years so as to fully appreciate the latest findings and key challenges relating to the topic addressed in the manuscript and to allow the authors to more clearly present their contributions to the pool of existing knowledge.
3. Some papers may help readers to broaden their horizons are listed below.
Unpacking the experienced utility of sustainable lifestyle guiding policies: A new structure and model. Sustainable Production and Consumption, 27: 486-495.
Interactive effects of two-way information and perceived convenience on waste separation behavior: Evidence from residents in eastern China. Journal of Cleaner Production, 374, 134032.
4. The authors said they extend the STIRPAT model. They should present the advantages of such improvement, both the method it self and the following results.
5. The discussion should be specific and detailed based on results found in this paper. The discussion usually contains a synthesis of the findings, the practical implications, the theoretical implications, the strengths and limitations of the research, and the future research directions. However, present discussion is really poor, and many contents are missing in this paper.
6. The implications are really general and have little guiding significance. The authors should improve this part.
Author Response
Please see the attachment
Author Response File: Author Response.pdf
Reviewer 3 Report
This paper presents forecasts for transportation CO2 emissions in shanghai. A regression model is calibrated using data from 2013-2019. The study assumes 5 scenarios based on population, wealth, and technology. The CO2 emissions in the 5 scenarios are forecasted. The study is interesting. My comments to further improve the paper are as follows:
More details (e.g., how the data is developed and reference to the data) are needed for the data sources (section 2.4) used to calibrate the regression model.
My understanding is that panel data is used here. I am not sure the ordinary least square model should be used.
Is the data used in validation (figure 3) also used in model calibration? If so, the validation is not very convincing.. The authors should use data not used in model calibration to validate the model.
The historical trend in Figure 3 should be discussed in detail. Particularly, whether the trend can be explained by the explanatory variables used in the model.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
I have no further comments
Reviewer 2 Report
the authors well addressed my concern.
Reviewer 3 Report
The authors only tried to address some of my previous comments. I don't think my 1st and 2nd comments are addressed; however, given the overall responses, I considered the authors have made reasonable efforts to address my previous comments.
