Optimizing the Hydrogen Supply Chain: Navigating Carbon Tax Scenarios for Fleet Decarbonization in Türkiye
水素サプライチェーンの最適化:トルコにおける炭素税シナリオと車両脱炭素化 (AI 翻訳)
Fidan Eser, Şule Itır Satoğlu
🤖 gxceed AI 要約
日本語
本研究は、異なる炭素税シナリオの下で水素サプライチェーンを最適化し、トルコの大型貨物輸送の脱炭素化を目指す。二目的多期間最適化モデルを用い、経済性と環境性のトレードオフを分析。結果、炭素税が高いほど水素コストが上昇するが、中央集権型チェーンでは再生可能エネルギーの割合が大幅に増加することを示した。
English
This study optimizes the hydrogen supply chain under alternative carbon tax scenarios to decarbonize heavy-duty freight in Türkiye. A bi-objective multi-period model reveals trade-offs between cost and emissions. Results show high carbon pricing increases hydrogen cost by 29% in hybrid designs and boosts renewable share from 2% to 47% in centralized chains. Sensitivity analysis indicates production cost variations affect LCOH but not network topology.
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
日本でも水素サプライチェーン構築とカーボンプライシングが議論されており、本論文の多期間最適化フレームワークは日本の地域水素ハブ設計や2030-2050年目標への示唆を与える。ただしトルコのデータに基づくため、日本への適用には条件調整が必要。
In the global GX context
This paper provides a comprehensive multi-period planning framework for hydrogen supply chains under carbon tax scenarios, applicable to emerging economies. It integrates policy milestones and quantifies how carbon pricing drives infrastructure investment. The framework can inform global hydrogen strategies, particularly for countries designing carbon pricing mechanisms to accelerate fleet decarbonization.
👥 読者別の含意
🔬研究者:Offers a novel bi-objective optimization model for hydrogen supply chain under carbon tax, with sensitivity analysis that can be replicated or extended.
🏢実務担当者:Provides insights for fleet operators and hydrogen infrastructure planners on cost and technology impacts of different carbon tax levels.
🏛政策担当者:Demonstrates how carbon tax scenarios influence hydrogen supply chain design, supporting evidence-based policy for decarbonizing heavy transport.
📄 Abstract(原文)
This study investigates how the hydrogen supply chain should be designed under alternative carbon tax scenarios to decarbonize heavy-duty freight transportation. A bi-objective, multi-period optimization model is developed to minimize the total daily system cost while constraining CO2 emissions using the Augmented ε-constraint approach, thereby revealing the trade-off between economic and environmental objectives. The model was applied to Türkiye’s heavy-duty transportation sector and solved under zero, moderate, and aggressive carbon tax scenarios. The results show that the levelized cost of hydrogen (LCOH) ranges from 2.06 to 14.06 $/kg H2. High carbon pricing increases the LCOH by 29.06% in hybrid designs, while raising the renewable energy share from 2.04% to 46.97% in centralized supply chains. Sensitivity analysis reveals that a ±20% variation in electrolyzer-based production costs does not alter the network topology but shifts the LCOH between 13.10 and 15.02 $/kg H2 in emission-focused solutions. The findings indicate that in renewable-energy-based decentralized structures, higher carbon tax policies primarily increase the LCOH. Still, the overall technology mix and network topology remain largely unchanged compared to the no-tax case. However, in centralized supply chains, carbon pricing affects both the energy sources and selected technologies. By integrating Türkiye’s 2030–2053 policy milestones into a multi-period framework, this study distinguishes itself by providing a comprehensive, multi-period planning framework tailored to the economic and logistical realities of developing countries. Unlike existing models, our approach quantifies how evolving carbon tax trajectories decisively drive infrastructure investment by analyzing the direct impact of different tax levels on the operational and strategic decisions of heavy-duty transport. This research represents the first joint assessment of carbon tax policy instruments and the evolution of long-term hydrogen supply chains, offering a decision-making framework for policy-driven energy transitions in similar emerging economies.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.3390/cleantechnol8030085first seen 2026-06-04 05:31:34
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