Navigating the Energy Trilemma in Green Steel: The Australian Case
グリーンスチールにおけるエネルギーのトリレンマへの対処：オーストラリアの事例 (AI 翻訳)
Anonymous, Author
🤖 gxceed AI 要約
日本語
本研究は、ハイブリッド多地域産業連関モデルを用いて、オーストラリアの鉄鋼業における脱炭素シナリオ（2024～2050年）の炭素フットプリント、価格、輸入依存度を分析。グリーンスチール移行におけるエネルギー・コスト・安全保障のトレードオフを定量的に示す。
English
This study uses a hybrid multi-regional supply-use model to compute carbon footprint, price, and import dependence of Australian steel across decarbonization scenarios (2024-2050). It quantifies the trade-offs between energy, cost, and security in the green steel transition.
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
日本鉄鋼業はグリーンスチールへの転換が急務。本論文のモデル手法は日本の地域別・技術別分析にも応用可能であり、SSBJやカーボンフットプリント開示の実務に示唆を与える。
In the global GX context
Steel decarbonization is a global challenge. This paper provides a rigorous quantitative framework for analyzing the energy trilemma, relevant for policymakers and industry navigating the EU CBAM, ISSB disclosures, and net-zero commitments.
👥 読者別の含意
🔬研究者:Methodology for integrated assessment of steel decarbonization using hybrid MRIO model is a valuable reference for future studies.
🏢実務担当者:Steel producers can use the scenario analysis to understand cost and supply risks of different decarbonization pathways.
🏛政策担当者:The trade-off insights inform industrial policy design for balancing emissions reduction, competitiveness, and energy security.
📄 Abstract（原文）
This repository accompanies the paper "Navigating the Energy Trilemma in Green Steel: The Australian Case" (currently submitted for peer review). It provides the full model code, the adjusted and extended hybrid Multi-Regional Supply-Use database, and the complete set of results, so that every quantitative finding of the paper can be reproduced starting from the public EXIOBASE hybrid Supply-Use database ( https://doi.org/10.5281/zenodo.7244918 ). The study uses a hybrid (mixed physical/monetary) Multi-Regional Supply-Use Table model, built on EXIOBASE and extended with explicit primary and secondary steelmaking technologies and Australian electricity-generation technologies, to compute the carbon footprint, price and import-dependence of Australian steel across decarbonisation scenarios (2024–2050). Contents code.zip — Full model code, the adjusted & extended MRSUT database ( database/baseline_aggr/ ), scenario inputs, auxiliary data, the figure-generation scripts, and a README documenting the end-to-end workflow (parse → aggregate → extend → scenario shocks → merge → plot). This is what a reader needs to regenerate all results directly from the public EXIOBASE data. GHG_Footprints_act.parquet — Steel GHG footprints (tonCO₂eq/ton steel) decomposed by activity of origin, for every scenario, year and sensitivity. GHG_Footprints_com.parquet — Steel GHG footprints by commodity/destination region. GHG_Footprints_com_EE.csv — Associated electricity-generation GHG footprint series (gCO₂eq/kWh). prices.parquet — Steel prices (EUR/ton steel) by region, scenario, year and sensitivity. Import_dependence.parquet — Import-dependence indicator (d_M), TPES and fuel-import results. Figures.zip — Figures of the paper. License: Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0), consistent with the upstream EXIOBASE v3.3.18 license.
🔗 Provenance — このレコードを発見したソース
- Zenodo https://zenodo.org/records/20719047first seen 2026-06-17 04:15:21 · last seen 2026-06-17 04:15:53
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