空間相関の視点から見た中国の小麦栽培カーボンフットプリントの省間格差と駆動メカニズム

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:LCAと機械学習を組み合わせた地域別炭素フットプリント推計と駆動要因の非線形分析の手法例として参考になる。

🏢実務担当者:食品・農業関連企業がサプライチェーン上流の農業排出を地域別に把握する際の推計アプローチとして活用できる。

🏛政策担当者:農業の低炭素化政策において、地域別ターゲティングと省間協調の設計に示唆を与える。

As one of the world’s most important staple crops, wheat plays a critical role in global food security, while the carbon emissions associated with its cultivation cannot be overlooked. However, existing studies have paid insufficient attention to the long-term and provincially consistent accounting of wheat cultivation carbon footprints, interprovincial spatial correlation, and the nonlinear responses and potential threshold effects of their driving factors. To address these limitations, this study estimated the provincial carbon footprint of wheat cultivation from 2000 to 2023 using a life cycle assessment (LCA) approach. Kernel density estimation, spatial correlation networks, Moran’s I, and the XGBoost-SHAP model were then employed for further analysis. The results show that: (1) the provincial carbon footprint of wheat cultivation exhibited significant spatial heterogeneity and stage-specific evolutionary characteristics during the study period. High-value areas were persistently concentrated in traditional major wheat-producing regions, such as North China and the Huang-Huai-Hai region, while the number of provinces with low carbon footprints generally increased; however, several major producing provinces continued to maintain relatively high levels. (2) The provincial carbon footprint showed significant positive spatial autocorrelation and formed a spatial correlation network centered on the Beijing-Tianjin-Hebei region, the Huang-Huai-Hai region, and the middle and lower reaches of the Yangtze River, exhibiting a stable and connected “core–periphery” structure. (3) Agricultural mechanization level and Planting structure were the dominant driving factors, with relative contributions of 35.7% and 31.2%, respectively, and both showed pronounced nonlinear and threshold effects. These findings suggest that carbon mitigation in China’s wheat cultivation should balance food security with low-carbon transformation. In particular, efforts should focus on optimizing planting structures and agricultural input patterns in high-footprint major producing areas, while strengthening cross-regional collaborative emission reduction through core provinces in the spatial correlation network, thereby improving resource-use efficiency and promoting low-carbon development in wheat production.

• openalex https://doi.org/10.1186/s13021-026-00535-0first seen 2026-11-12 05:11:06 · last seen 2026-11-14 05:16:22