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System dynamics model of refuse-derived fuel adoption in Indonesia's cement industry: model file and simulation dataset

インドネシアのセメント産業におけるRDF導入のシステムダイナミクスモデル:モデルファイルとシミュレーションデータセット (AI 翻訳)

Ummatin, Kuntum Khoiro, Hidayatno, Akhmad, Setiawan, Andri, Abubakar, Muhammad Afzal Syahrahman

Zenodoデータセット2026-08-10#エネルギー転換経営インパクト: コスト削減対象セクター: cement
DOI: 10.5281/zenodo.21866680
原典: https://zenodo.org/records/21866680

🤖 gxceed AI 要約

日本語

本データセットは、インドネシアのセメント産業におけるRDF(廃棄物由来燃料)導入のシステムダイナミクスモデルとシミュレーション出力を提供する。モデルは人口、MSW発生、RDF採用、生産、需要、CO2回避の6モジュールで構成され、2026年から2045年までの政策シナリオを評価する。政策手段としてチッピング料金とTSR目標を組み込み、低・中・高の準備状態条件を考慮する。

English

This dataset provides a system dynamics model and simulation outputs for refuse-derived fuel (RDF) adoption in Indonesia's cement industry. The model comprises six modules: population, MSW generation, RDF adoption, production, demand, and avoided CO2 emissions, evaluating policy scenarios from 2026 to 2045. It incorporates policy instruments such as tipping fees and TSR targets under varying readiness conditions.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

日本では廃棄物発電やセメント産業の脱炭素化が進むが、本モデルはインドネシアの政策設計に焦点を当てており、日本の読者には東南アジアの廃棄物管理と産業連携の事例として参考になる。

In the global GX context

This dataset contributes to global GX scholarship by providing a replicable system dynamics model for RDF adoption in emerging economies, relevant to circular economy and waste-to-energy transitions. It offers insights for policymakers and industries in developing countries seeking to reduce landfill emissions and coal use.

👥 読者別の含意

🔬研究者:GX研究者は、廃棄物由来燃料の導入モデルと政策シナリオ分析の方法論を参考にできる。

🏢実務担当者:セメント業界のサステナビリティ担当者は、RDF導入のコストとCO2削減効果の評価に活用できる。

🏛政策担当者:政策担当者は、チッピング料金やTSR目標などの政策手段の効果を定量的に評価する際に参考になる。

📄 Abstract(原文)

================================================================================ System dynamics model of refuse-derived fuel adoption in Indonesia's cement industry: model file and simulation dataset ================================================================================ ASSOCIATED ARTICLE ------------------ Ummatin KK, Hidayatno A, Setiawan AD, Abubakar MAS. Readiness-Contingent Policy Design for Refuse-Derived Fuel Adoption in Indonesia's Cement Industry: A Scenario-Based System Dynamics Analysis. Submitted to Clean Technologies and Environmental Policy (Springer). [Article DOI to be added on publication] Corresponding author: Akhmad Hidayatno Systems Engineering, Modeling and Simulation Laboratory, Department of Industrial Engineering, Faculty of Engineering, Universitas Indonesia, Depok, Indonesia E-mail: [email protected] CONTENTS -------- RDF_adoption_model.mdl     Vensim model file, plain-text format. Six modules: population,     MSW generation, RDF adoption, RDF production, RDF demand, and     avoided CO2 emissions. Readable in any text editor. RDF_adoption_model.2mdl     Same model, Vensim binary format. run_baseline.vdfx     Simulation run output (Vensim binary dataset format). annual_simulation_outputs.xlsx     Annual simulation outputs, 2026-2045, for every condition and     instrument combination reported in the article. Sheets:       README                - run settings and units       Baseline_by_condition - no-policy baseline, three conditions       Low Readiness         - four instruments       Circular Transition   - four instruments       Enabling Ecosystem    - four instruments       Validation            - behaviour-reproduction test data       Cumulative_summary    - cumulative RDF and avoided CO2 Supplementary_Information_FIX.docx     Supplementary Information accompanying the article. Contains the     stock-and-flow structure of each of the six modules (Figs. S1-S6)     and the complete model formulation (Tables S1-S6): every variable,     its dimension, unit, and defining equation, including the values of     all model constants. NOTE ON PARAMETERS ------------------ All parameter values used in the simulations are given in two places: Tables S1-S6 of the Supplementary Information, and the model file itself, which is plain text and lists every constant and lookup function. No separate parameter spreadsheet is required to reproduce the results. MODEL SETTINGS -------------- Software        Vensim (PLE or higher; the .mdl file opens in any version) Initial time    2020 Final time      2045 Time step       0.25 year Integration     Euler Spatial scope   East Java province, Indonesia HOW TO REPRODUCE ---------------- 1. Open RDF_adoption_model.mdl in Vensim. 2. Set the readiness condition by applying the per-capita waste    generation, RDF yield, and coal price ranges given in Table 2 of the    article. 3. Apply an instrument: tipping fee Rp100,000/t or Rp200,000/t, or the    TSR target trajectory rising from 10% to 50% over 2025-2045. 4. Run to 2045. Outputs should match annual_simulation_outputs.xlsx. Figures 5 to 8 of the article are generated directly from annual_simulation_outputs.xlsx. NOTES AND LIMITATIONS --------------------- - Avoided-emission factors are held constant in the model   (1.96 t CO2/t RDF landfill methane; 2.0 t CO2/t RDF coal displacement).   Emission results are therefore structural model outputs, not   empirically calibrated values, and await independent life-cycle   validation. - RDF yield is an exogenous scenario condition, not an endogenous   variable. - The model represents East Java and is not calibrated to other   Indonesian provinces. COPYRIGHT AND LICENCE --------------------- (c) 2026 The Authors (K.K. Ummatin, A. Hidayatno, A.D. Setiawan, M.A.S. Abubakar). Made available under CC BY 4.0. Data and documentation:  CC BY 4.0 Model file:              CC BY 4.0 You are free to share and adapt this material for any purpose, provided appropriate credit is given to the authors and to the associated article. CITATION -------- Ummatin KK, Hidayatno A, Setiawan AD, Abubakar MAS (2026) System dynamics model of refuse-derived fuel adoption in Indonesia's cement industry: model file and simulation dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21866680

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