A scenario-based framework linking biophysical soil carbon modeling to illustrative economic signals
生物物理学的土壌炭素モデリングと例示的な経済シグナルを結びつけるシナリオベースのフレームワーク (AI 翻訳)
Ayomikun David Ajayi, Wiyao Banakinaou, Tadao Aoda, Hideo Hasegawa
🤖 gxceed AI 要約
日本語
本研究は、新潟県の温帯アンドソル地域を対象に、保全農業、慣行耕作、有機農業の3つの農業システムにおける土壌有機炭素(SOC)動態を20年間シミュレーションし、炭素税、補助金、キャップ&トレードの3つの炭素価格政策のもとで正味現在価値(NPV)を評価した。中程度の気候シナリオ(SSP2-4.5)では、保全農業が最も高いNPVを示した(3%割引率、中程度の価格経路で286ドル/ha)。フレームワークは透明で再現可能な政策分析ツールを提供するが、結果は例示的なものであり、実際の導入インセンティブを予測するものではない。
English
This study simulates soil organic carbon (SOC) dynamics over 20 years for three farming systems in Niigata, Japan, under two climate pathways. It translates SOC changes into net present value (NPV) under carbon tax, subsidy, and cap-and-trade. Conservation agriculture yields highest NPV ($286/ha at 3% discount rate under moderate pricing). The framework offers transparent policy analysis but results are illustrative, not predictive.
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
日本において農業分野のカーボンクレジット制度(J-クレジットなど)や炭素価格政策の設計に直接関連する。特に、土壌炭素貯留の経済的価値を定量化する手法を提示しており、SSBJや企業のサステナビリティ開示における農業関連のスコープ1・2・3排出量の評価にも示唆を与える。
In the global GX context
This paper provides a transparent framework linking soil carbon modeling to carbon pricing, relevant for global climate policy design (e.g., carbon markets, agricultural offsets). It demonstrates how biophysical outputs can inform economic signals, supporting decisions under TCFD/ISSB-aligned scenario analysis. The case study in Japan adds region-specific insights for temperate Andosol systems.
👥 読者別の含意
🔬研究者:The framework offers a reproducible method to connect SOC modeling with economic analysis, useful for further research on agricultural carbon policy interactions.
🏢実務担当者:Illustrative NPV results can help agricultural advisors communicate potential revenue from carbon farming practices under different policy designs.
🏛政策担当者:Provides a transparent tool for comparing carbon pricing instruments in agriculture, highlighting sensitivity to model parameters and discount rates.
📄 Abstract(原文)
Soil organic carbon (SOC) sequestration offers climate mitigation potential in agriculture, yet linking biophysical soil carbon dynamics to policy-relevant interpretation remains challenging. This study develops and demonstrates a transparent, scenario-based framework to explore how alternative carbon policy signals could translate into relative, illustrative economic responses in temperate agricultural systems: A Plot-Scale Case Study. SOC dynamics were simulated over 20 years (2025–2045) for Conservation Agriculture (CA), Conventional Tillage (CT), and Organic Farming (OF) in a temperate Andosol region of Niigata, Japan, under two CMIP6 climate pathways (SSP2–4.5 and SSP5–8.5). Modeled SOC changes were translated into illustrative economic signals using three carbon pricing instruments: carbon tax, subsidy, and cap-and-trade, and assessed through a Net Present Value (NPV) framework with discount rate sensitivity analysis. Under moderate climate forcing (SSP2–4.5), CA, CT, and OF sequestered carbon at 0.09, 0.08, and 0.06 t C ha −1 yr −1 , respectively. CA consistently generated the highest NPV across pricing scenarios ($286 ha −1 at 3% discount rate under a moderate price trajectory). Under the high-emissions SSP5–8.5 scenario, the model projected differential responses across systems. These varying responses are directly related to the calibrated fractions of inert organic matter, rather than empirically validated differences in climate vulnerability. The proposed framework provides a transparent and reproducible approach for exploring how soil carbon dynamics interact with alternative policy instrument designs under explicit biophysical and climate assumptions. Results are intended as illustrative scenario outputs for comparative policy analysis, not as forecasts of adoption incentives or market behaviour. • A transparent framework links process-based SOC modeling with stylized carbon policy scenarios. • Economic outcomes represent gross carbon-revenue signals under exogenous price assumptions. • Conservation agriculture shows higher modeled carbon-revenue potential under selected scenarios. • Climate response differences are strongly influenced by model structure and parameterization. • Framework supports comparative exploration of policy scenarios rather than policy prescription.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1016/j.agsy.2026.104791first seen 2026-05-28 04:44:17 · last seen 2026-06-03 04:43:34
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