気候変動緩和シナリオにおける炭素除去のためのバイオ炭生産モデリングの技術経済学と価値判断
Techno-economics and value judgments of modeling biochar production for carbon removal in climate change mitigation scenarios (原題)
Tabea Dorndorf, Nikolas Hagemann, Anne Merfort, Sabine Fuss, Jessica Strefler
🤖 gxceed AI 要約
日本語
統合評価モデル（IAM）におけるバイオ炭生産のモデリングに内在する技術経済的考慮と価値判断を明示化。生産構成を職人的、移動式、確立、先進工業の4分類に分け、パラメータ化の楽観度が展開に与える影響を1.5℃シナリオで検証。地質CO2貯留の仮定が主要因であることを示す。
English
This paper jointly presents techno-economic considerations and value judgments in modeling biochar production for carbon removal in the IAM REMIND. It classifies production configurations and tests cautious vs. optimistic assumptions, finding that geologic CO2 storage assumptions dominate deployment, but biochar parameterization and advanced configurations also matter. Highlights the need for transparent modeling practices.
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
日本では、バイオ炭は炭素除去技術として注目されつつあり、J-クレジット制度での活用も検討されている。本論文は、モデル前提の透明性向上に寄与し、日本の気候政策におけるバイオ炭の位置づけを検討する際の示唆を与える。
In the global GX context
Globally, biochar is gaining attention as a carbon dioxide removal (CDR) option. This paper contributes to the transparency of IAM assumptions, relevant for IPCC assessments and national climate strategies. It underscores the importance of value judgments in modeling emerging technologies, informing policy expectations.
👥 読者別の含意
🔬研究者:IAMモデリングにおけるバイオ炭の扱いと価値判断の影響を理解するための枠組みを提供。
🏢実務担当者:バイオ炭プロジェクトの経済性評価や炭素除去クレジットの設計に示唆。
🏛政策担当者:気候シナリオにおける技術前提の透明性確保の重要性を示す。
📄 Abstract（原文）
Integrated assessment models (IAMs) create policy-relevant expectations about emerging technologies. Their modeling requires a stylized representation of many possible technological futures, which involves value judgments. Acknowledging calls for reflection on value-laden assumptions, we jointly present the techno-economic considerations and value judgments in modeling biochar production and its use for carbon removal in the IAM REMIND. Our framework distinguishes between the selection of technology configurations and their parameterization. For biochar, we first introduce a classification of production configurations into artisanal, mobile, established, and advanced industrial categories. In selecting biochar configurations, value judgments are embedded in assumptions of equivalence and fungibility with other mitigation options, given the socio-political and carbon permanence differences between them. Modelers also have to decide whether to include established or more advanced configurations that deliver greater systemic value but are associated with higher uncertainty. For parameterization, our data collection shows a wide range of quotable assumptions, providing scope for different levels of optimism. We then test the impact of cautious versus optimistic biochar production assumptions on biochar deployment in scenarios limiting climate change to low overshoot above 1.5 °C. The primary determinant of deployment is not the parameterization of biochar production, but rather assumptions about geologic CO 2 storage, which constrain the deployment of competing BECCS technologies. Nonetheless, biochar parameterization and the inclusion of an advanced, currently non-existent, configuration also influence deployment. The analysis highlights how technological framing and assumptions shape modeled technology potentials, underscoring the need for transparent and reflexive modeling practices.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.erss.2026.104882first seen 2026-09-05 05:05:32
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