Green Hydrogen for Public Transportation: Insights From an ABM and From Palma de Mallorca Case Study
公共交通機関のためのグリーン水素：エージェントベースモデルとパルマ・デ・マヨルカのケーススタディからの洞察 (AI 翻訳)
Roberta De Cristofaro, C. Ponsiglione, S. Primario
🤖 gxceed AI 要約
日本語
本論文は、グリーン水素バリューチェーンの複雑性を捉えるエージェントベースモデルを提案し、パルマ・デ・マヨルカの事例に適用。政策立案者が脱炭素目標下での投資シナリオを評価するための枠組みを提供し、技術・政策・市場動態がバリューチェーンのパフォーマンスと回復力に与える影響を分析する。
English
This paper proposes an agent-based model to capture the complexity of green hydrogen value chains and applies it to a case study in Palma de Mallorca. The model supports policymakers in evaluating investment scenarios under decarbonization goals, analyzing how technology, policy, and market dynamics affect performance and resilience.
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
日本は水素基本戦略を掲げ、運輸部門でのグリーン水素活用を推進している。本モデルは、複数主体の調整や政策効果のシミュレーションに有用であり、日本の自治体や事業者が水素導入を検討する際の参考になる。
In the global GX context
Green hydrogen is central to global decarbonization efforts, especially in hard-to-abate transport sectors. This ABM provides a flexible tool for policymakers to simulate coordination challenges and investment outcomes, contributing to evidence-based planning for hydrogen infrastructure deployment worldwide.
👥 読者別の含意
🔬研究者:The agent-based model offers a novel approach to simulate complex value chain dynamics, useful for researchers studying hydrogen transitions.
🏢実務担当者:Corporate sustainability teams can use the model to evaluate investment scenarios and coordination risks in hydrogen projects.
🏛政策担当者:Policymakers can leverage the model to test policy settings and design support mechanisms for green hydrogen deployment.
📄 Abstract（原文）
The development of green hydrogen (GH2) value chains is crucial for decarbonizing sectors such as transport and industry. Their emergence, however, requires coordination among diverse actors, technologies, and regulations, which traditional analytical approaches struggle to capture. This study introduces an agent‐based model (ABM) that reflects the complexity of GH2 value chains and supports policymakers in evaluating investment scenarios under decarbonization and energy transition goals. The model integrates heterogeneous agent behaviors, innovation dynamics, and sustainability certification mechanisms, assessing performance across environmental, social, and economic dimensions. By capturing feedback loops, coordination challenges, and trade‐offs, it enables more informed and sustainable decision‐making. The ABM is applied to a real‐world GH2 value chain case study, demonstrating how technologies, policy settings, and market dynamics influence its performance and resilience over time. By offering actionable insights within a flexible simulation environment, this work supports evidence‐based planning and contributes to shaping the GH2 transition.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/bse.70761first seen 2026-05-15 19:29:52
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