Data and code for "Carbon trading steers China's steel decarbonisation while mitigating inter-plant profit inequality"
「炭素取引が中国の鉄鋼脱炭素を導き、工場間の利益不平等を緩和する」のデータとコード (AI 翻訳)
Shansen Wei
🤖 gxceed AI 要約
日本語
本リポジトリは、中国の鉄鋼脱炭素化と炭素取引の影響を分析した論文のデータ・コード・出力を提供する。工場レベルの空間明示モデルを用い、石炭からガス、水素への段階的移行、水素・CCSの展開、省間炭素排出枠フロー、利益不平等を評価する。再現性向上と炭素市場設計の研究支援を目的とする。
English
This repository provides data, code, and outputs for a study on China's steel decarbonisation under carbon trading. Using a plant-resolved, spatially explicit model, it analyzes the coal-to-gas-to-hydrogen transition, hydrogen and CCS deployment, interprovincial carbon allowance flows, and inter-plant profit inequality. It aims to enhance transparency and support further research on plant-level steel decarbonisation and carbon market design.
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
中国の鉄鋼産業の脱炭素経路と炭素市場設計の実証分析は、日本の鉄鋼業界やカーボンプライシング政策に示唆を与える。特に、工場レベルの利益格差を考慮した政策設計は、日本のGX推進における公正な移行の参考になる。
In the global GX context
This empirical analysis of China's steel decarbonisation and carbon trading offers insights for global carbon market design and industrial transition. The plant-level modeling approach and focus on profit inequality contribute to the literature on just transition and carbon pricing, relevant for ISSB-aligned disclosure and transition finance.
👥 読者別の含意
🔬研究者:Provides a reproducible model and data for plant-level steel decarbonisation and carbon market analysis.
🏢実務担当者:Offers insights into carbon trading impacts on steel plant profitability and technology pathways, useful for corporate strategy.
🏛政策担当者:Demonstrates how carbon trading can steer industrial decarbonisation while addressing inter-plant inequality, informing policy design.
📄 Abstract（原文）
This repository contains the data, model code and raw optimization outputs supporting the article “Carbon trading steers China’s steel decarbonisation while mitigating inter-plant profit inequality”. The repository includes three main components. First, it provides plant-level and spatial data for Chinese steel plants, low-carbon hydrogen supply nodes, CO₂ utilization and geological storage sites, and the potential transport connections among these facilities. Second, it contains the Python source code used to formulate and solve the plant-resolved, spatially explicit and dynamic steel decarbonisation model with Gurobi. Third, it provides raw model outputs for different mitigation targets, carbon-price trajectories, carbon-trading settings and technology-cost assumptions. These materials support the analysis of the staged coal–gas–hydrogen transition in China’s iron and steel industry, the spatial deployment of hydrogen and carbon capture and storage technologies, interprovincial carbon allowance flows, sector-wide lifecycle profit and inter-plant profit inequality. They are provided to improve the transparency and reproducibility of the study and to support further research on plant-level steel decarbonisation and carbon-market design.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.21786083first seen 2026-08-06 04:54:56 · last seen 2026-08-06 04:54:58
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。