Carbon‑removal opportunities and constraints of bioenergy crops on marginal croplands in China
中国の限界農地におけるバイオエネルギー作物の炭素除去の機会と制約 (AI 翻訳)
Ting Hua, Yi Yang, M. Rama Krishna, Han Wang, Hui Wu, Z Q Zhang, Manuel Delgado-Baquerizo
🤖 gxceed AI 要約
日本語
中国の限界農地3600万haを対象に、衛星データと空間明示的生産性モデルを用いてバイオエネルギー作物の炭素除去ポテンシャルと制約を評価。年間1.88〜2.09EJのバイオ燃料供給と192〜298百万トンのCO2正味除去が可能で、自然再生のみと比べ最大76%の追加除去効果。ただし、限界農地の約半数が生物多様性優先地域と重なるため、配置制約が重要。
English
Assesses bioenergy crop potential on 36 million ha of marginal croplands in China using satellite data and spatially explicit yield modeling. Finds 1.88–2.09 EJ yr⁻¹ biofuel and 192–298 Mt CO₂ yr⁻¹ net carbon removal, up to 76% beyond natural regrowth. Highlights constraints from biodiversity overlap and the need for optimized crop selection and CCS.
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
日本のバイオマス戦略や農地活用政策にとって、限界農地の炭素除去ポテンシャル評価手法が参考になる。特に、SSBJやカーボンクレジット制度との連携において、土地利用型除去の定量化は重要。ただし中国事例であり、日本の農地面積・気候条件との違いに注意。
In the global GX context
Provides a spatially explicit, data-driven framework for assessing bioenergy carbon removal potential, directly relevant to national climate strategies under the Paris Agreement. Findings on biodiversity trade-offs inform global debate on land-based mitigation, aligning with ISSB and TCFD guidance on nature-related disclosures.
👥 読者別の含意
🔬研究者:Methodology combining satellite data with yield and CCS modeling offers a replicable framework for assessing bioenergy potential in other regions.
🏢実務担当者:Insights on crop selection, irrigation vs. CCS trade-offs help inform bioenergy project planning and carbon credit strategies.
🏛政策担当者:Quantifies the contribution of marginal croplands to national climate targets and highlights biodiversity constraints, crucial for land‑use policy design.
📄 Abstract（原文）
Bioenergy crops present a promising solution for climate mitigation and clean energy, yet national-scale deployment is constrained by land availability, crop suitability, water resources, carbon capture and storage, and competing environmental priorities. Here, we combine satellite-based land-cover data with spatially-explicit yield model to assess the leverages, constraints and land–energy–carbon nexus of bioenergy deployment on 36 million hectares marginal croplands in China. This strategy could supply 1.88–2.09 EJ yr⁻¹ biofuel and deliver 192–298 million tonnes CO₂ yr⁻¹ net carbon removal—up to 76% over natural regrowth alone—with minimal risks to water scarcity or biodiversity. It could offset 8–12% of agri-food emissions and meet 15–17% of transport-energy demand. Nearly half of marginal cropland overlaps with biodiversity-priority areas, posing critical constraints on deployment, where natural regrowth serves as a preferable alternative. Optimizing crop selection, and carbon capture and storage consideration are more critical for enhancing outcomes than irrigation alone. Bioenergy crops on China’s marginal croplands could increase net carbon removal by up to 76% beyond natural regrowth alone with limited water and biodiversity impacts, based on satellite land-cover data and spatially explicit yield modeling.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1038/s43247-026-03588-8first seen 2026-05-31 05:28:27 · last seen 2026-06-03 05:06:10
🔔 こうした論文の新着を逃したくない方は キーワードアラート に登録（無料・3キーワードまで）。
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。