米国炭素排出における農業・都市化・生態系脆弱性の相互作用経路：カーボンニュートラルと気候ガバナンスへの示唆
Interactive pathways of agriculture, urbanization, and ecosystem vulnerability in U.S. carbon emissions: insights for carbon neutrality and climate governance (原題)
Fanhao Yang, Jianya Zhao, Zijia Luo, Xingchen Gu, Shu Wang
🤖 gxceed AI 要約
日本語
米国1995〜2022年の排出データとND-GAINを統合し、農業・都市化・生態系脆弱性の相乗効果を多次元で分析。ガウス近似でEKC仮説を検証し一人当たりGDP約4万ドルに変曲点を確認、PLSRがR²=0.869で優位。食料脆弱性と都市集中は排出抑制、農業生産力と水脆弱性は排出促進に働く。STIRPATシナリオでは生態系回復が約1.29%減、適応型農業は短期に約3.44%増と推計。
English
Integrating ND-GAIN with U.S. emission inventories (1995–2022), this study models synergistic effects of agriculture, urbanization, and ecosystem vulnerability on carbon emissions. Gaussian fitting supports the EKC with an inflection near $40,000 GDP per capita, while PLSR (R²=0.869) reveals nonlinear interactions: food vulnerability and urban concentration suppress emissions, whereas agricultural capacity and water vulnerability drive them. STIRPAT scenarios show ecological restoration cuts emissions ~1.29%, while adaptive agriculture raises them ~3.44% short-term.
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SSBJ・有報開示が主戦場であり、本稿は直接の開示論点を持たない。ただし自治体・地域脱炭素や農業系企業のScope 3・土地利用評価を考える際の参照枠として、多システム統合の分析視角は示唆的。
In the global GX context
Adds to global climate-governance scholarship by quantifying cross-system interactions (agriculture, urbanization, ecosystem vulnerability) that single-factor EKC and STIRPAT models miss, relevant to land-sector accounting under ISSB/CSRD and to national adaptation planning.
👥 読者別の含意
🔬研究者:EKC・STIRPAT分析に多変量非線形相互作用を持ち込む手法設計の参考になる。
🏢実務担当者:農業・土地利用由来の排出や適応策の短期トレードオフをScope 3・TCFDシナリオ検討に反映する示唆。
🏛政策担当者:生態系回復と適応型農業の排出影響が逆方向である点を、地域脱炭素計画の政策設計に留意すべき。
📄 Abstract（原文）
Abstract The complex interdependencies among agricultural systems, urbanization, and ecosystem vulnerability represent critical yet underexplored determinants of carbon emissions. To move beyond single-factor analyses, this study constructs a multidimensional framework to quantify the synergistic effects of these factors on U.S. carbon emissions from 1995 to 2022. By integrating data from The Notre Dame Global Adaptation Initiative (ND-GAIN) with national emission inventories, we adopt a multi-method analytical approach: Gaussian fitting validates the Environmental Kuznets Curve (EKC) hypothesis, through which an inflection point is identified at a per capita GDP of about $40,000, while the results also reveal the model’s limitations in capturing policy-induced nonlinearities. Partial least squares regression (PLSR) exhibits superior explanatory power with an R² value of 0.869 compared to ridge regression, and its latent component analysis further uncovers significant nonlinear interactions. Key findings show that food vulnerability and urban concentration act as significant suppressors of carbon emissions, whereas agricultural production capacity and water vulnerability function as major driving factors. Scenario simulations based on the Stochastic Impacts by Regression on Population, Affluence and Technology model further confirm the emission-reducing effect of ecological restoration, which leads to an approximate 1.29% decrease in carbon emissions, while also indicating that adaptive agriculture development may result in a short-term increase of about 3.44%. This study underscores the necessity of multi-system governance, proposes a “natural restoration-technological innovation-institutional synergy” policy framework, and provides a data-driven pathway for U.S. carbon neutrality as well as a novel paradigm for multi-scale climate governance analysis.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1007/s10668-026-08239-8first seen 2026-10-31 04:56:47 · last seen 2026-11-06 04:48:05
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