From Map to Policy: Road Transportation Emission Mapping and Optimizing BEV Incentives for True Emission Reductions

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript studies the importance of regional factors in emission reduction by analyzing the spatial heterogeneity of German passenger car data. The research shows that the regional strategy combined with the two calculation methods can achieve the emission reduction targets in the transportation field more efficiently. The manuscript provides enough background knowledge and all the relevant reference materials, the charts are novel, the analysis is reasonable, and the results are basically clear. However, the following content needs to be modified.

1. Lines 231-234. When integrating KBA and ADAC data, the manuscript does not discuss data missing or inconsistent issues, please supplement and improve.
2. Lines 289-298. The manuscript does not elaborate on how to deal with the aggregation of geographical boundaries, please supplement and improve.
3. Lines 349-350. Figure 5 does not explain the iterative termination condition of the algorithm, please supplement and improve.
4. Lines 350-356. The manuscript does not add a discussion on the applicability of the algorithm, which can be applied to other countries with similar traffic characteristics, please modify.
5. Lines 475-481. The manuscript does not discuss in depth the results of regional analysis, such as why some regions show higher emission reduction potential, please supplement and improve.
6. Lines 477-481. The manuscript does not further explore the implementation difficulty and practical feasibility of the optimization strategy, please modify.
7. Lines 569-571. The manuscript does not specify the impact of limitations on the research results, please supplement and improve.

Author Response

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Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

The article presents an insightful analysis of regional differences in passenger car emissions in Germany and explores the impact of battery electric vehicle (BEV) allocation. The presentation is good. However, it requires significant technical improvements to enhance its scientific rigor, validation, and comparability. 

• Check the caption of Figure 1 and others. It seems the caption is a continuation of the text. 

• The study does not clearly outline the computational models or algorithms used for regional emission estimations and BEV allocation. A well-defined mathematical or simulation-based approach should be included, along with justification for chosen parameters and assumptions.

• The article does not provide a comparative analysis with other available models or studies on regional emissions and BEV deployment. A literature review or at least a benchmark comparison would strengthen the study’s credibility.

• There is no validation of the proposed spatial allocation algorithm. Sensitivity analysis on key variables such as fleet replacement rates, vehicle efficiency, and electricity mix should be conducted to ensure robustness.

• While regional variations are mentioned, statistical confidence levels, uncertainties in input data, and potential biases in vehicle stock classification should be addressed. Providing a more detailed breakdown of data sources and potential limitations is necessary.

• The reported emission reduction of 1.66% to 1.35% lacks context. A comparison with national GHG reduction targets and alternative BEV penetration scenarios would provide a clearer perspective on the effectiveness of the approach.

•  The study assumes a simplistic regional allocation without discussing real-world driving behavior, charging infrastructure availability, or variations in regional energy mixes. These factors significantly influence BEV impact and should be incorporated for a more comprehensive assessment.

• The differences between WtW and TtW emissions are mentioned but not analyzed in depth. A more detailed discussion on how electricity generation sources affect WtW emissions should be provided, including a scenario where Germany’s grid evolves towards more renewables.

• The article should connect its findings to policy recommendations or real-world implementation strategies. How feasible is the suggested BEV allocation model? What incentives or regulatory measures could support optimal vehicle distribution?

Author Response

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Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors

The paper name is "from map to policy: road transportation emission mapping and

optimizing BEV incentives for true emission reductions". Overall, the manuscript is well-structured, written, and has clear figures. However, there are some comments on how to improve the paper's quality. The comments are:

1. Would you specifically model the impact of future grid carbon reduction scenarios on BEVs' WtW footprint?
2. Think about sensitivity analyses: what would happen if the composition of the electrical grid changed more quickly or more slowly than anticipated?
3. Because there aren't any more recent statistics, the authors utilize data from 2017, yet as you pointed out, yearly mileage has decreased since then. Could you give an uncertainty range for these estimations or utilize data that has been forecasted?
4. Comparing your findings to comparable BEV allocation research from other nations (such as case studies on spatial EV incentives from the US or the EU) would be beneficial.
5. A formal flowchart for the allocation algorithm is required. Please replace Figure 5.
6. Please, provide detailed discussions on the policy implications based on your findings.

Author Response

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Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

It is an interesting work that analyzes the impact of private vehicles, their technology and the expected levels of emissions according to the routes and regions. I recommend its publication. Some clarifications are made since the 2017 base case is used. 8 years ago seems to me to be a very long period, perhaps it is not possible to extrapolate to the current situation? On the other hand, it is recommended to define the concepts TtW and WtW from the beginning so that the study is more understandable.

In the introduction it is mentioned that electric vehicles do not represent local emissions, but the impact of the emissions is global. Later, it is apparently considered in the analysis. Clarify this.

Author Response

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Author Response File: Author Response.docx

Reviewer 5 Report

Comments and Suggestions for Authors

The paper presents a novel analysis of road transportation emissions in Germany. The paper’s subject is topical, and the research results can be used to establish future policies to reduce emissions from road transport. The paper is well structured. The methodology is clearly explained, as are the results obtained. Therefore, I consider that the article can be accepted for publication, with the following observations:

- the phrase in lines 188-192 contains 2 almost identical sentences

- in the explanation in fig. 2, at the end I think the word “used” is missing

- in lines 456-457 it is written “For both, and WtW, emissions are reduced by replacing conventional cars with electric ones.” I think that after the comma it should be written WtT.

Author Response

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Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

All of my concerns have been properly resolved. This manuscript can be accepted.

Author Response

Dear Reviewer,

 

Thank you for your note and your effort!

Reviewer 2 Report

Comments and Suggestions for Authors

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Author Response

Dear Reviewer,

 

Thank you for your time and effort, we have appreciated your comments on the work and tried our best to cover all of them accordingly.