Pathways to Industrial Decarbonization in Thailand Toward Net-Zero 2050
タイにおける2050年ネットゼロに向けた産業脱炭素化の道筋 (AI 翻訳)
W. Wangjiraniran, N. Nakapreecha, J. Pongthanaisawan
🤖 gxceed AI 要約
日本語
タイの産業部門のネットゼロ達成に向けたモデルベースの経路を分析。LEAPフレームワークを用いて9つのサブセクターを3つのシナリオで評価。政策実施と低炭素技術導入の速度が排出量に大きく影響し、「ビジョン目標」シナリオでは2065年にネットゼロに達する可能性があるが、早期の技術導入が必要。「バランス成長」シナリオでは2050年以前のネットゼロが可能だが、2025-2030年のピークが必要。政策と技術の統合が重要。
English
This study develops model-based pathways for Thailand's industrial sector to achieve net-zero emissions using the LEAP framework. Analyzing nine subsectors under three scenarios, it finds that policy enforcement and technology adoption speed are key. The Visionary Goal scenario reaches net-zero by 2065, while the Balancing Growth scenario could achieve it before 2050 if emissions peak by 2025-2030. The Path of Challenge scenario shows net-zero unattainable. The paper underscores the need for coherent industrial policies and early commercialization of hydrogen and CCUS.
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
本論文はタイの産業脱炭素化経路をモデル化しており、日本のGX政策やアジアでの排出削減戦略に参考となる。特に、政策実施の重要性と水素・CCUSの早期商業化の必要性は日本にも示唆を与える。
In the global GX context
This paper provides a comprehensive modeling framework for industrial decarbonization in an emerging economy. It contributes to the growing literature on net-zero pathways by integrating policy scenarios and technology diffusion. The findings are relevant for countries designing their industrial decarbonization strategies, especially in Asia.
👥 読者別の含意
🔬研究者:Useful for modelers and policy analysts working on industrial decarbonization pathways and integrated assessment models.
🏢実務担当者:Corporate sustainability teams in Thailand or companies operating in Thailand can use these scenarios for long-term decarbonization planning.
🏛政策担当者:Thai policymakers can leverage the results to inform the Climate Change Act and align industrial policies with net-zero targets.
📄 Abstract（原文）
This study develops model-based pathways for achieving net-zero greenhouse gas emissions in Thailand’s industrial sector, integrating policy foresight with quantitative energy system modeling. Using the Low Emission Analysis Platform (LEAP) framework, nine industrial subsectors were analyzed under three transition scenarios—Path of Challenge, Visionary Goal, and Balancing Growth—to assess the techno-economic feasibility of decarbonization through 2065. The model incorporates structural transformation, technology diffusion, and policy enforcement parameters to simulate future energy demand and emission trajectories. Results highlight that policy enforcement and the pace of low-carbon technology adoption are the dominant determinants of industrial emission outcomes. Under the Visionary Goal scenario, which aligns with current national policy direction, Thailand could reach net-zero emissions by 2065; however, this requires an accelerated GHG reduction rate and early deployment of high-impact technologies such as hydrogen and carbon capture, utilization, and storage (CCUS). The Balancing Growth scenario, emphasizing rapid industrial restructuring and early technology commercialization, demonstrates a potential to achieve net-zero before 2050, contingent on industrial emissions peaking between 2025–2030. Conversely, the Path of Challenge scenario—characterized by delayed technology uptake and limited policy intervention—shows that the net-zero target becomes unattainable, with cumulative emissions exceeding the allowable carbon budget by over 30 MtCO₂e. The findings underscore the need for coherent long-term industrial and energy policies that simultaneously promote innovation, strengthen institutional mechanisms such as the forthcoming Climate Change Act, and incentivize early commercialization of emerging technologies. Integrating policy ambition with targeted technology acceleration is essential for Thailand’s industrial sector to align with national and global net-zero trajectories.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.32479/ijeep.22756first seen 2026-05-06 00:00:57
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。