炭素循環の不確実性と野心的緩和経路における土地利用変化排出の役割

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🔬研究者:IAMと炭素循環モデルの結合における炭素密度パラメータ化の重要性と、予算効果と密度効果の独立性という方法論的知見を提供する。

🏢実務担当者:ネットゼロ目標やCDR・森林クレジット調達戦略の前提が持つ不確実性を感度分析で示す材料になる。

🏛政策担当者:残存炭素予算や土地利用排出の不確実性を踏まえ、炭素価格・吸収源政策の設計に幅を持たせる必要性を示す。

The carbon cycle and its sensitivity to different forcings is a major source of uncertainty in scenario assessments of Earth System Models (ESMs) on climate change. However, while the relevant carbon cycle uncertainties are often an important part of ESM assessments, they are currently poorly and inconsistently accounted for in the derivation of mitigation pathways using Integrated Assessment Models (IAMs). Here, we incorporate carbon cycle data from 9 different Dynamic Global Vegetation Models (DGVMs) into the REMIND-MAgPIE-MAGICC IAM framework, using the DGVM model diversity as the main source of uncertainty, and assess variations in scenario outcomes derived from them. We show that varying only assumptions about the carbon density potentials of vegetation types leads to important variations in the cost-effective deployment of land-based mitigation solutions. In scenarios where warming is limited to 1.7°C, cumulative landuse change emissions (2020-2050) vary from negative to substantially positive (-12 to 57 GtCO2), with a 30% variation in carbon prices, 100 Mha in forest area and a substantially different CDR mix. By calibrating the simple climate model MAGICC to reproduce the land carbon and nitrogen fluxes from these same DGVMs, we also consistently assess the uncertainty in the remaining carbon budget to limit warming to 1.7°C due to the varied responses of the carbon sink to environmental changes. We find that, although this budget effect in terms of cumulative emissions (a spread of 280 GtCO2) is much larger than the density effect, the two effects are not significantly correlated. The budget effect can therefore still be assessed with the climate emulator alone, as is current practice, whereas the density effect requires varying carbon densities in the IAM and adds to the budget effect. The results point to the need for a more consistent and systematic approach to the parametrization of carbon densities in IAM assessments.

• openalex https://doi.org/10.22541/essoar.15009904/v1first seen 2026-10-25 04:38:22 · last seen 2026-11-04 04:38:33