Re-Evaluating Agricultural Carbon Efficiency Across Functional Grain Zones: From Spatial Analysis
機能的な穀物ゾーンにおける農業炭素効率の再評価：空間分析から (AI 翻訳)
Miaoling Bu, Wei Xi, Lin Mi, Mingyang Gao, Guofeng Wang
🤖 gxceed AI 要約
日本語
本研究は中国の穀物機能ゾーン（生産・消費・均衡）における農業炭素排出効率を2003-2022年で評価。超効率EBM-GMLモデルと空間ダービンモデルを用い、効率の地域差と波及効果を分析。結果、均衡ゾーンの効率が最も高く、効率的資源配分は隣接地域に正の波及効果をもたらす一方、自然災害は負の効果を生む。
English
This study evaluates agricultural carbon emission efficiency across China's functional grain zones (production, consumption, balanced) from 2003-2022 using a super-efficient EBM-GML model and spatial Durbin model. Results show systematic differences, with the balanced zone having highest efficiency. Efficient resource allocation creates positive spillover effects, while natural disasters weaken them.
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
日本では農業分野のGHG削減が求められる中、中国の地域別炭素効率評価手法は参考になる。ただし、日本の農業構造や地域区分とは異なるため、直接適用には注意が必要。
In the global GX context
This paper provides a methodological framework for assessing regional agricultural carbon efficiency and spatial spillovers. The findings could inform integrated carbon reduction policies for agriculture in countries with diverse regional conditions.
👥 読者別の含意
🔬研究者:Methodological approach (EBM-GML, spatial Durbin) applicable to agricultural carbon efficiency studies in other regions.
🏢実務担当者:Insights on regional carbon efficiency differences could guide agricultural resource allocation, though China-specific.
🏛政策担当者:Spatial spillover effects emphasize the need for coordinated regional policies to reduce agricultural carbon emissions.
📄 Abstract（原文）
Regional reassessments of agricultural carbon emission efficiency are essential for improving the sustainability of food production systems under climate constraints. This study evaluates agricultural carbon emission efficiency (ACEE) across China’s major grain-producing zone (GPZ), major grain-consuming zone (GSZ), and grain production–consumption balanced zone (GBZ) during 2003–2022, excluding Hong Kong, Macao, Taiwan, and Tibet due to data limitations. A super-efficient EBM–GML model incorporating both desirable and undesirable outputs is employed to measure ACEE at the provincial level, with comparisons conducted within each functional zone and nationally unified efficiency values used as a benchmark. Spatial dependence is examined using Moran’s I, and a spatial Durbin model is applied to identify driving factors and spatial spillover effects. The results indicate that the average efficiency levels differ systematically across functional grain zones, following the order GBZ > GPZ > GSZ, while several provinces experience notable changes in their relative rankings. Carbon emissions increase in the earlier period and decline in later years, whereas efficiency exhibits an opposite temporal pattern, reflecting a gradual transition of grain production systems from extensive input-driven growth toward more sustainability-oriented practices. Substantial regional disparities in ACEE are also observed. Rational industrial organization and efficient allocation of production resources contribute to positive spillover effects on neighboring regions, whereas natural disasters and inefficient resource distribution tend to weaken such effects. These findings suggest that functional grain zones provide an effective framework for capturing intra-regional heterogeneity and should be adopted as the basic unit for efficiency assessment and the formulation of differentiated governance strategies.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.3390/land15040571first seen 2026-06-29 07:55:26
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