Carbon Innovation Pathway to a Green Future: Steps to Achieving Net Zero in Africa
グリーンな未来への炭素革新経路:アフリカでのネットゼロ達成へのステップ (AI 翻訳)
Princewill Odum, Joshua Jonah Kunda, Francis E. Bisong, Pauline Essoka
🤖 gxceed AI 要約
日本語
本論文は、アフリカがネットゼロ移行の主導者となる可能性を探る。9層の統合フレームワークを提示し、モロッコ、ケニア、ルワンダ、南アフリカ、エチオピア、モザンビークの事例を分析。技術的には2050年までのネットゼロ達成は可能だが、気候金融の再構築、Article 6炭素市場の実施、ジェンダー平等と先住民知識の統合が必要と主張。
English
This paper explores Africa's potential as a leader in the net-zero transition, presenting a nine-tier integrated framework. It analyzes case studies from six African countries and argues that net zero by 2050 is technically feasible but requires restructuring global climate finance, implementing Article 6 carbon markets, and integrating gender equity and indigenous knowledge.
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
アフリカのネットゼロ経路に関する包括的フレームワーク。日本の二国間クレジット制度(JCM)やArticle 6市場への示唆があるが、直接的な政策連動は限定的。
In the global GX context
This paper offers a comprehensive framework for Africa's net-zero transition, highlighting the need for reformed climate finance and robust carbon markets. It contributes to global discourse on equitable transition and the role of developing countries in climate action.
👥 読者別の含意
🔬研究者:Provides a systematic framework and case studies for understanding Africa's net-zero pathways.
🏢実務担当者:Offers actionable recommendations for each tier of the framework, useful for companies and investors engaging in African carbon markets.
🏛政策担当者:Highlights policy gaps and recommends reforms in climate finance and carbon market mechanisms.
📄 Abstract(原文)
Africa contributes less than 4% of cumulative global greenhouse gas emissions, yet faces disproportionate and intensifying climate impacts across all five sub-regions. Simultaneously, the continent possesses 60% of the world's best solar resources, 30% of global critical minerals, and the youngest growing workforce on earth. This is a convergence of endowments that positions Africa not merely as a victim of climate change but as a potential architect of the global net-zero transition. This paper presents a systematic analysis of Africa's carbon innovation pathway to net zero, structured around a nine-tier integrated framework encompassing enabling governance foundations, energy transition, land and nature-based solutions, industrial decarbonisation, carbon removal technologies, carbon markets and finance, digital and innovation enablers, social equity and just transition, and climate resilience and adaptation. Drawing on a robust review of most recent peer-reviewed literature published between 2020 and 2026, supplemented by institutional data from the IPCC, IEA, IRENA, UNFCCC, African Development Bank, and African Union, the paper critically evaluates global net zero successes and their applicability to African contexts, identifies structural barriers facing African nations, and adaptable success stories from Morocco, Kenya, Rwanda, South Africa, Ethiopia, and Mozambique as model trajectories. A theoretical framework integrating Innovation Systems Theory, Climate Justice Theory, and the Just Transition Framework is applied to interrogate the equity dimensions of the transition. The paper argues that achieving net zero in Africa by 2050 is technically feasible but requires a fundamental reimagining of global climate finance architecture, robust implementation of Article 6 carbon markets, accelerated deployment of geospatial AI for Monitoring, Reporting and Verification (MRV), and uncompromising integration of gender equity, indigenous knowledge, and community energy as structural, non-peripheral pillars of the transition. Policy-actionable recommendations are provided for each tier of the framework.
🔗 Provenance — このレコードを発見したソース
- crossref https://doi.org/10.37284/ajccrs.5.1.5051first seen 2026-05-30 05:30:38 · last seen 2026-06-03 05:53:44
- semanticscholar https://doi.org/10.37284/ajccrs.5.1.5051first seen 2026-06-02 05:12:36 · last seen 2026-06-03 05:15:51
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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。