技術進歩による農業炭素排出の時空間的進化・デカップリング特性・駆動メカニズムに関する研究—中国四川省21市州のパネルデータによる実証
Study on Spatiotemporal Evolution, Decoupling Characteristics and Driving Mechanism of Agricultural Carbon Emissions from Technological Progress—Panel Evidence from 21 Prefectures (States) in Sichuan Province, China (原題)
Lin Wang, Qin Chen
🤖 gxceed AI 要約
日本語
四川省21市州の2015〜2024年パネルデータを用い、農地利用・水田メタン・作物栽培・稲わら焼却・畜産から農業炭素排出を算出。SDEモデルで時空間パターンを、Tapioデカップリングモデルで農業経済との関係を分析した。農業技術進歩は肥料投入強度の低下を通じて排出を有意に抑制するが、その効果は平野部と非民族農業地域に限定され、民族地域や非平野山間部では機械化だけでは排出削減が困難であることを示した。
English
Using 2015–2024 panel data from 21 prefectures in Sichuan, China, this study calculates agricultural carbon emissions across farmland use, paddy methane, crop cultivation, straw burning and livestock. SDE and Tapio decoupling models reveal spatial patterns and a fluctuating strong/weak decoupling with the agricultural economy. Panel regression shows technological progress significantly curbs emissions partly via lower fertilizer intensity, but effects are regionally heterogeneous and mechanization alone fails in ethnic and mountainous areas.
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
日本のGX文脈では、農業分野のScope 3・サプライチェーン排出(食品・農業関連企業の一次産業排出把握)や、地域別の脱炭素政策設計の参考になる。SSBJ開示におけるバリューチェーン上流排出の算定手法を考える際の示唆がある。
In the global GX context
Adds sub-national empirical evidence on agriculture-economy decoupling and the limits of technology-driven mitigation, relevant to global discussions on land-sector emissions accounting under GHG Protocol and CSRD value-chain reporting, and to food-system transition finance.
👥 読者別の含意
🔬研究者:農業排出の地域別デカップリングと技術進歩の媒介・調整効果を定量化した実証枠組みとして参照できる。
🏢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し、肥料投入や作付集約度を排出削減レバーとして評価する際に有用。
🏛政策担当者:地域別の農業脱炭素政策設計において、機械化依存の限界と地域エンドウメントに応じた差別化支援の必要性を示す。
📄 Abstract(原文)
Against the dual goals of agricultural and rural carbon emission reduction, carbon sequestration and food security guarantee, this paper uses municipal panel data of 21 prefectures in Sichuan Province from 2015 to 2024 to calculate agricultural carbon emissions from multiple dimensions including farmland utilization, paddy field methane, crop cultivation, straw burning and livestock breeding. The standard deviational ellipse model (SDE) is adopted to reveal the spatiotemporal pattern of agricultural carbon emissions, and the Tapio decoupling model is applied to identify the decoupling relationship between agricultural carbon emissions and the agricultural economy. A panel model is constructed. The Breusch–Pagan Lagrange Multipkier (LM) test and Hausman test are performed to select the random-effects model to examine the impact of agricultural technological progress on agricultural carbon emissions. Robustness tests and grouped heterogeneity analysis are carried out. Furthermore, mediation and moderation models are introduced to identify the internal transmission paths and boundary conditions. The results show that: (1) From 2015 to 2024, the total agricultural carbon emissions in Sichuan Province generally declined. Animal husbandry was the primary emission source while carbon emissions from crop cultivation showed an upward trend, and carbon emission intensity kept decreasing. The spatial pattern of agricultural carbon emissions presented strong path dependence; the emission centroid remained stable in the central basin with a northeast–southwest spatial distribution. (2) The relationship between agricultural carbon emissions and the agricultural economy in Sichuan Province fluctuated alternately between strong decoupling and weak decoupling. Sustained and stable strong decoupling has not yet been achieved, and the incremental emissions from crop cultivation constitute a key factor disturbing the decoupling state. (3) Benchmark regression results indicated that agricultural technological progress significantly curbed regional agricultural carbon emissions, and urbanization also exerted emission-reduction effects. The proportion of primary industry, land scale operation and grain planting ratio significantly increased agricultural carbon emissions, whereas rural residents’ income and agricultural industrial structure showed no significant impacts. The carbon emission reduction effect of agricultural technological progress, constrained by regional endowments, presented notable regional heterogeneity. The emission reduction effect of technological progress was significant in plain and non-ethnic farming areas, while it was difficult to achieve emission reduction merely by relying on mechanization in ethnic regions and non-plain mountainous areas. (4) Mechanism tests demonstrated that fertilizer application intensity played a partial mediating role between agricultural technological progress and agricultural carbon emissions. Agricultural technological progress can indirectly reduce carbon emissions by lowering fertilizer application intensity. The multiple cropping index exerted a positive moderating effect. The higher the multiple cropping index, the stronger the inhibitory effect of agricultural technological progress on agricultural carbon emissions. This paper identified key regions, core emission reduction targets and directions for technological optimization for differentiated low-carbon agricultural governance in Sichuan Province, and provided empirical evidence for developing agriculture-specific carbon emission reduction plans tailored to local conditions. It also clarified the limits of the emission reduction effectiveness of agricultural technological advancements across different regions. The research findings can provide precise guidance for the green and low-carbon transformation of regional agriculture, assist local governments in addressing weaknesses in agricultural emission reduction efforts and mitigate risks such as rising emissions from crop cultivation and rebound effects from decoupling.
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- semanticscholar https://doi.org/10.3390/land15101961first seen 2026-10-17 05:37:19 · last seen 2026-11-06 05:51:50
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