Evaluating the Potential of Sustainable Aviation Fuel for Decarbonization of the Aviation Sector: An Agent-based Model
航空部門の脱炭素化のための持続可能な航空燃料（SAF）の可能性評価：エージェントベースモデル (AI 翻訳)
Geeta Joshi, Tejeswi Ramprasad, Harmandeep Singh, Narayanan Rajaraman, Vikrant Urade, Arnoud Higler, Rajagopalan Srinivasan
🤖 gxceed AI 要約
日本語
本論文は、持続可能な航空燃料（SAF）の普及を評価するエージェントベースモデルを開発し、インドの民間航空システムに適用した。結果は、SAFの採用はインフラ整備と価格形成が重要であり、単なる政策義務だけでは不十分であることを示した。パッセンジャーの需要反応も影響を与える。このモデルは政策と市場の不確実性下での現実的な移行戦略評価に有用である。
English
This paper develops an agent-based model to analyze sustainable aviation fuel (SAF) transition pathways, applied to India's civil aviation system. Results show that SAF adoption depends on infrastructure coordination and price formation, not just policy mandates. Passenger demand feedback further influences outcomes. The model demonstrates the value of agent-based approaches for evaluating realistic decarbonization strategies under uncertainty.
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
日本でも航空部門の脱炭素化が課題となっており、本論文のエージェントベースモデルはインフラと価格形成の連携の重要性を示しており、日本のSAF政策やインフラ計画に示唆を与える。ただし、インドのデータに基づくため直接適用には注意が必要。
In the global GX context
This paper provides a novel agent-based modeling framework for aviation decarbonization that integrates infrastructure, market, and policy dynamics. It highlights the critical role of infrastructure coordination and price formation, which are relevant to global SAF policy discussions. The model is particularly useful for countries developing national SAF strategies.
👥 読者別の含意
🔬研究者:Useful for researchers studying energy transition modeling, especially agent-based models for sectoral decarbonization.
🏢実務担当者:Aviation fuel suppliers and airlines can use insights on infrastructure timing and cost learning for investment decisions.
🏛政策担当者:Policymakers can leverage the model to understand the interplay of mandates and infrastructure in achieving SAF adoption targets.
📄 Abstract（原文）
The aviation sector represents one of the most pressing challenges in the energy transition due to its strong reliance on energy-dense liquid fuels and established fuel infrastructure. Sustainable Aviation Fuel (SAF), particularly from agricultural residues, offers a near-term mitigation pathway; however, large-scale adoption is shaped by policy mandates, infrastructure expansion, market price formation, and passenger demand responses. These coupled dynamics are difficult to capture using aggregate or equilibrium-based models. This study develops an agent-based model to analyze SAF transition pathways and applies it to India’s civil aviation system. Results show that SAF adoption emerges from the coordination between infrastructure entry, cost learning, and market responses rather than mandate ambition alone. Even moderate mandates fall short of intended adoption levels without timely infrastructure expansion, while aggressive mandates become infeasible under binding supply and price constraints. Passenger demand feedbacks further influence outcomes by linking fuel cost increases to airline operations and route-level allocation decisions. The findings highlight infrastructure coordination and price formation as critical leverage points for aviation decarbonization and demonstrate the value of agent-based models for evaluating realistic SAF transition strategies under policy and market uncertainty.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.69997/sct.197646first seen 2026-06-20 06:46:05 · last seen 2026-06-21 05:33:01
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