System Dynamics Modeling of Cement Industry Decarbonization Pathways: An Analysis of Carbon Reduction Strategies

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The paper presents an excellent and very well-timed study that suggests an interesting and well-grounded approach to feasibility evaluation of various aspects of carbon emissions mitigation in cement industry. System dynamic modelling definitely holds much promise for assessment of technological solutions as candidate Best Available Techniques, which makes this method extremely interesting for practitioners, regulatory bodies and other stakeholders.

As possible improvements/suggestions for further research I should note the following:
- when discussing current trends in carbon emissions from the cement industry (specifically alternative fuels), standardized GHG Protocols under Cement Sustainability Initiative (CSI) are neglected, such as 'CO₂ Accounting and Reporting Standard for the Cement Industry' (2005) and more importantly, corresponding International Standard ISO/DIS 19694-3 (2023);
- regarding SCM - please, consider concrete demolition waste. This may provide an additional dimension to the scenarios by closing the material cycle in construction industry.

Minor issues to be noted in the presented manuscipt: please, add values in Figures 1 and 6-11 to make them more informative (at present, the charts look more like rough drafts). 'Plus' and 'Minus' signs in System dynamics models need to be bigger - at present, they are quite difficult to read. Also, the index at CO2 in Line 61 is not sub-scipt.

Other than mentioned above, in my opinion, the paper has no flaws and may be accepted to print.

Author Response

Thank you for the feedback!  We truly appreciate your comments, and have used them to strengthen our paper:

Comment 1: The paper presents an excellent and very well-timed study that suggests an interesting and well-grounded approach to feasibility evaluation of various aspects of carbon emissions mitigation in cement industry. System dynamic modelling definitely holds much promise for assessment of technological solutions as candidate Best Available Techniques, which makes this method extremely interesting for practitioners, regulatory bodies and other stakeholders.

Response 1: Thank you!

Comment 2: As possible improvements/suggestions for further research I should note the following:
- when discussing current trends in carbon emissions from the cement industry (specifically alternative fuels), standardized GHG Protocols under Cement Sustainability Initiative (CSI) are neglected, such as 'CO₂ Accounting and Reporting Standard for the Cement Industry' (2005) and more importantly, corresponding International Standard ISO/DIS 19694-3 (2023);

Response 2: We added that into the alternative fuels discussion. Thank you!

Comment 3: Regarding SCM - please, consider concrete demolition waste. This may provide an additional dimension to the scenarios by closing the material cycle in construction industry.

Response 3: We have added that in.  That was an excellent suggestion!

Comment 4: Minor issues to be noted in the presented manuscipt: please, add values in Figures 1 and 6-11 to make them more informative (at present, the charts look more like rough drafts). 'Plus' and 'Minus' signs in System dynamics models need to be bigger - at present, they are quite difficult to read. Also, the index at CO2 in Line 61 is not sub-scipt.

Response 4: We have corrected those issues.

Reviewer 2 Report

Comments and Suggestions for Authors

(1) Significant concerns exist regarding the paper's overall rigor and scientific foundation. Notable examples include the citation formatting used in the Introduction section and the way the core scientific problem is framed and introduced.

(2) The paper’s Introduction section should integrate both research background and literature review. The current narrative lacks coherence and reorganizing this section to establish a clear research context is essential.

(3) The System Dynamics model suffers from critical shortcomings:

①Unjustified Simplification: No theoretical/empirical basis for oversimplified assumptions;

②Inadequate Element Justification: Variables and feedback loops lack rationale for inclusion;

③Incomplete Mathematical Framework: Key components (equations, parameters, initial conditions) are undefined;

④Missing Experimental Design: Model validation (e.g., sensitivity analysis, historical fit) and scenario simulations are undescribed.

(4) Figures 7–11 exhibit strikingly similar curve patterns, lacking descriptions of the data and their sources.

(5) The results presented in the article are mainly qualitative descriptions, lacking specific quantitative indicators and data support.

(6) The references are not sufficient. There are many cases where research conclusions have not been cited. The author should further improve the references to ensure that they cover the latest research progress in this field.

Author Response

Thank you for the review.  We truly appreciate your feedback and the opportunity to correct our paper to make it stronger and more relevant to the field.  Please see below for our responses:

Comment 1: Significant concerns exist regarding the paper's overall rigor and scientific foundation. Notable examples include the citation formatting used in the Introduction section and the way the core scientific problem is framed and introduced.

Response 1: We have updated the paper significantly.  In particular, we restructured the background section, combining material.  We also put effort into making sure that the core scientific problem is framed and introduced.

Comment 2: The paper’s Introduction section should integrate both research background and literature review. The current narrative lacks coherence and reorganizing this section to establish a clear research context is essential.

Review 2: We have incorporated that into the background section. And corrected that portion to make it clearer.

Comment 3: The System Dynamics model suffers from critical shortcomings:

①Unjustified Simplification: No theoretical/empirical basis for oversimplified assumptions;

②Inadequate Element Justification: Variables and feedback loops lack rationale for inclusion;

③Incomplete Mathematical Framework: Key components (equations, parameters, initial conditions) are undefined;

④Missing Experimental Design: Model validation (e.g., sensitivity analysis, historical fit) and scenario simulations are undescribed.

Response 3: We have significantly updated our system dynamics discussion and model.  In particular, we provided more background information. Additionally, we provided the full mathematical framework, giving the stocks/flows and the mathematical framework, much of which is based on historical data and literature.

Comment 4: Figures 7–11 exhibit strikingly similar curve patterns, lacking descriptions of the data and their sources.

Response 4: The initial paper set out to be more qualitative with these figures. However, based on your feedback and other reviewers' feedback, this was deemed inappropriate. So instead, we made them quantitative, showing the actual output from the system dynamics models.

Comment 5: The results presented in the article are mainly qualitative descriptions, lacking specific quantitative indicators and data support.

Response 5: That was the initial goal of the paper.  However, we have adjusted the results to make them quantitative.

Comment 6: The references are not sufficient. There are many cases where research conclusions have not been cited. The author should further improve the references to ensure that they cover the latest research progress in this field.

Response 6: We added a number of references to ensure that we are capturing the latest research in the field.

Reviewer 3 Report

Comments and Suggestions for Authors

The article "System Dynamics Modeling of Cement Industry Decarbonization Pathways: An Analysis of Carbon Reduction Strategies" presents a system dynamics model that evaluates the long-term impact of three key decarbonization strategies in the cement industry: the use of low-carbon fuels, carbon capture and storage (CCS), and supplementary cementitious materials (SCMs) to reduce clinker content. 

The manuscript is clearly written, logically structured, and highly relevant to the field of industrial decarbonization. The modeling approach is appropriate for the research goals, and the paper effectively illustrates the complex relationships between technology choices, economic impacts, and regulatory conditions. The references, although limited in number, are mostly recent and well-selected. There is no indication of excessive self-citation.

The methodology is explained in sufficient detail to ensure reproducibility, and the system dynamics diagrams are well-crafted and easy to follow. However, the paper’s main weakness lies in the presentation of the results. Figures 6 to 11 show only general directional trends without any numerical values—neither absolute nor relative—which prevents the reader from making meaningful comparisons between the scenarios. Without a quantitative reference, it is impossible to assess the magnitude of the differences in emissions, costs, or effectiveness across strategies.

This lack of numerical data also weakens the conclusions. Each scenario is treated in isolation, rather than being compared side by side using a common metric or framework. Including at least normalized or relative values (e.g., percentage change in emissions, cost per ton of CO₂ avoided) would allow for a more robust evaluation of trade-offs and synergies between approaches. A comparative table or overlayed graphs would significantly enhance the clarity and analytical strength of the findings.

Moreover, adding a simple numerical example—such as applying the model to a hypothetical or real cement plant—would make the model’s usefulness more concrete and allow readers to better grasp the practical implications. While the system is conceptually strong, the lack of even illustrative data limits its applicability and hinders the ability to generalize or validate the results.

In summary, this is a valuable and timely study that applies a suitable and innovative modeling approach to an urgent climate challenge. The structure and clarity of the paper are commendable, and the system model is well constructed. However, to fully justify its conclusions and increase its contribution to the field, the article should include numerical or at least relative data in its results, enable a direct comparison of scenarios, and, if possible, provide a worked example to demonstrate the model in context. With these improvements, the manuscript would be a strong candidate for publication.

Author Response

Comment 1: The manuscript is clearly written, logically structured, and highly relevant to the field of industrial decarbonization. The modeling approach is appropriate for the research goals, and the paper effectively illustrates the complex relationships between technology choices, economic impacts, and regulatory conditions. The references, although limited in number, are mostly recent and well-selected. There is no indication of excessive self-citation.

Response 1: Thank you!

Comment 2: The methodology is explained in sufficient detail to ensure reproducibility, and the system dynamics diagrams are well-crafted and easy to follow. However, the paper’s main weakness lies in the presentation of the results. Figures 6 to 11 show only general directional trends without any numerical values—neither absolute nor relative—which prevents the reader from making meaningful comparisons between the scenarios. Without a quantitative reference, it is impossible to assess the magnitude of the differences in emissions, costs, or effectiveness across strategies.

Response 2: This comment was in line with many of the other reviewer's concerns.  You are correct.  While the original goal was to be qualitative, the impact is much stronger with quantitative numbers.  So we provided additional details about the model and provided numbers for the cost and carbon reduction with each strategy.

Comment 3: This lack of numerical data also weakens the conclusions. Each scenario is treated in isolation, rather than being compared side by side using a common metric or framework. Including at least normalized or relative values (e.g., percentage change in emissions, cost per ton of CO₂ avoided) would allow for a more robust evaluation of trade-offs and synergies between approaches. A comparative table or overlayed graphs would significantly enhance the clarity and analytical strength of the findings. Moreover, adding a simple numerical example—such as applying the model to a hypothetical or real cement plant—would make the model’s usefulness more concrete and allow readers to better grasp the practical implications. While the system is conceptually strong, the lack of even illustrative data limits its applicability and hinders the ability to generalize or validate the results.

Response 3: Great suggestion!  After making the analysis more quantitative, we added a section comparing the different strategies.

Comment 4: In summary, this is a valuable and timely study that applies a suitable and innovative modeling approach to an urgent climate challenge. The structure and clarity of the paper are commendable, and the system model is well constructed. However, to fully justify its conclusions and increase its contribution to the field, the article should include numerical or at least relative data in its results, enable a direct comparison of scenarios, and, if possible, provide a worked example to demonstrate the model in context. With these improvements, the manuscript would be a strong candidate for publication.

Response 4: Thank you for the suggestions!  They were insightful and useful.  We concurred with all of your recommendations and implemented the changes throughout the paper.

Reviewer 4 Report

Comments and Suggestions for Authors

Model Transparency and Reproducibility 

The manuscript lacks a description of stock and flow equations, model logic or underlying assumptions. Figure 3-5 illustrate causal loops but not the models quantitative architecture. The authors should provide a complete technical appendix with: governing equations and flow logic; parameter values (Source, units, baseline values), Time horizon and integration method, what software platform was used. Without this, the model is not scientifically verifiable or replicable. 

Quantitative Simulation results

The scenario presented are entirely qualitative. No graghs to depict emission reductions over time, cement cost projections or sensitivity bands. please include numerical simulations showing: Emission (eg Mt CO2/year), cement cost changes ($/ton), Demand elasticity and response time, Time-bound trajectories (eg 2005 -2050).  This will allow policy makers and academics to evaluate trade-offs with greater confidence.

Literature contribution 

• Prior system dynamics studies such as Ige et al. 2022, Anand et al. 2006, Kunche & Mielczarek 2021) have modeled similar dynamics with national calibration and policy layers.
• The novelty of the manuscript can be enhanced by;
• Benchmarking the model against one national case study (US or EU).
• Introduction of policy levers such as carbon tax, subsidies,  regulation-induced adoption thresholds
• Policy and Stakeholder Mapping

      The model could have been more robust if the influence of regulatory and economic instruments that are central to real-world decarbonisation was not omitted. 

A stakeholder or actor-based influence map (government, industry, cement associations) would improve relevance and broaden impact.

•    Figures and Visualisation 

Figures 3–11 are schematic and lack labeled axes, units, time intervals, or scale references.

Please enhance all system dynamics plots with:

• • Time-series axes (e.g., 2025–2050),

  • Emissions in Mt CO₂ or kg CO₂ per ton of cement,

  • Cost in $/ton cement.

Additional suggestions for strengthening the manuscript 

• Introduce a  policy impact matrix linking strategy combinations to outcomes (triple bottom line: economic, environmental, societal).Conflict of interest: Acknowledge if any restrictions from the U.S. Department of Defense affect access to modeling inputs or outputs. 

Comments on the Quality of English Language

While the manuscript is grammatically sound and readable, several sections—particularly those describing the model structure, scenario analysis, and implications—lack precision, clarity, and academic fluency. Specifically:

• Ambiguous phrasing (e.g., “the model was used to evaluate a number of scenarios”) could be made more rigorous and specific.

• Technical descriptions are sometimes overly simplified, which may lead to misinterpretation of the system dynamics approach.

• Transitional logic between paragraphs is occasionally weak, affecting the cohesion of arguments.

A light professional language edit focused on academic clarity, technical precision, and logical flow would elevate the quality significantly.

Author Response

Before addressing each of your comments individually, I wanted to thank you for your insight.  When I first read your review, I was a bit concerned about the amount of revisions required.  As we were working through the revisions, everything fell into place, and it was actually a lot of fun making these revisions!  We feel that the updated paper is much stronger, and I want to thank you for your insights.

Comment 1: The manuscript lacks a description of stock and flow equations, model logic or underlying assumptions. Figure 3-5 illustrate causal loops but not the models quantitative architecture. The authors should provide a complete technical appendix with: governing equations and flow logic; parameter values (Source, units, baseline values), Time horizon and integration method, what software platform was used. Without this, the model is not scientifically verifiable or replicable. 

Response 1: The original goal of our paper was to be qualitative in nature. However, after your review (and the other reviews), we realized that with our models, we should definitely present quantitative results.  We added a section into the paper with the stock/flows and equations to increase the transparency.  We also provided substantially more background information to show where the information came from.

Comment 2: The scenario presented are entirely qualitative. No graghs to depict emission reductions over time, cement cost projections or sensitivity bands. please include numerical simulations showing: Emission (eg Mt CO2/year), cement cost changes ($/ton), Demand elasticity and response time, Time-bound trajectories (eg 2005 -2050).  This will allow policy makers and academics to evaluate trade-offs with greater confidence.

Response 2: This has been changed in the updated version to align with your recommendation.

Comment 3: Prior system dynamics studies such as Ige et al. 2022, Anand et al. 2006, Kunche & Mielczarek 2021) have modeled similar dynamics with national calibration and policy layers. The novelty of the manuscript can be enhanced by Benchmarking the model against one national case study (US or EU), Introduction of policy levers such as carbon tax, subsidies,  regulation-induced adoption thresholds, 

Response 3: We added discussion about policy levers into the background and analysis sections.  That was a great suggestion. In particular, we had information about how much each of these measures would raise the cost of cement. That really helps frame the problem for carbon taxes as an incentivization.

Comment 4: The model could have been more robust if the influence of regulatory and economic instruments that are central to real-world decarbonisation was not omitted.  A stakeholder or actor-based influence map (government, industry, cement associations) would improve relevance and broaden impact.

Response 4: We attempted to better capture this in our stock/flow discussion that we added.  We also added additional discussion into the background section.

 

Comment 5: Figures 3–11 are schematic and lack labeled axes, units, time intervals, or scale references. Please enhance all system dynamics plots with Time-series axes (e.g., 2025–2050), Emissions in Mt CO₂ or kg CO₂ per ton of cement, Cost in $/ton cement.

Response 5: Done!

Comment 6: Introduce a  policy impact matrix linking strategy combinations to outcomes (triple bottom line: economic, environmental, societal).

Response 6: While we did not include a policy impact matrix, we did include additional discussion about policies in both the background, model, and analysis sections.

Comment 7: Acknowledge if any restrictions from the U.S. Department of Defense affect access to modeling inputs or outputs. 

Response 7: There were not restrictions in place.  I wasn't sure if we need to annotate in the conflict of interest section.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The response and revision meet well with the comments. It can be accepted with the current version.

Reviewer 4 Report

Comments and Suggestions for Authors

All the feedback given have been done. The paper can be accepted