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Spatial–Temporal Characteristics, Driving Factors, and Future Trends of Carbon Emissions from Crop Farming in the Yangtze River Economic Belt, China

長江経済帯の作物栽培からの炭素排出の時空間特性、駆動要因、将来予測 (AI 翻訳)

Yongjun Cai, Jun Ren, Huan Yang, Chengying Li, Yonghao Wang, Lei Li, Shuqi Wang, Shengzhe Zhu

Land📚 査読済 / ジャーナル2026-04-03#炭素会計Origin: CN
DOI: 10.3390/land15040593
原典: https://doi.org/10.3390/land15040593

🤖 gxceed AI 要約

日本語

中国長江経済帯の11省（市）における2013-2024年の作物栽培由来の炭素排出を分析。メタン排出が最大で、農薬・肥料由来は減少、土壌由来は増加。効率改善が最大の削減要因、経済発展が増加要因。将来は排出量と強度ともに減少傾向だが地域差あり。

English

This study analyzes carbon emissions from crop farming in China's Yangtze River Economic Belt (2013-2024). Methane from paddy fields is the largest source; emissions from agricultural inputs decline while soil emissions rise. Efficiency improvements are the main driver for reduction, while economic development increases emissions. Future projections show declining emissions and intensity, but regional pressures remain.

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

日本では農林水産省の「みどりの食料システム戦略」に相当するが、本論文は中国の地域データを用いており、日本に直接適用可能な知見は限られる。ただし、排出係数法やLMDIモデルなどの手法は日本の農業分野のGX評価にも応用可能。

In the global GX context

This paper provides empirical evidence on agricultural carbon emissions trends and drivers in China, relevant for global efforts to decarbonize agriculture. The methods (LMDI, Tapio decoupling) are transferable, though the specific context is China's Yangtze River Economic Belt.

👥 読者別の含意

🔬研究者:Provides a methodological framework for analyzing agricultural carbon emissions trends and driving factors.

🏢実務担当者:Can inform agricultural sustainability teams about key emission sources and decoupling patterns, but note the China-specific context.

🏛政策担当者:Highlights the importance of efficiency improvements and structural adjustments for agricultural decarbonization, relevant for designing agricultural green transformation policies.

📄 Abstract（原文）

Carbon emissions from crop farming are a critical component of carbon emissions from land use. This study focuses on crop farming in the Yangtze River Economic Belt. The carbon emission coefficient method, the LMDI model, the Tapio decoupling model, and the GM(1,1) gray forecasting model were employed to systematically analyze the spatiotemporal evolution, driving mechanisms, decoupling effects, and future trends of carbon emissions from crop farming in the Yangtze River Economic Belt, based on panel data from 11 provinces (municipalities) covering the period 2013–2024. The results show that the total carbon emissions from crop farming in the Yangtze River Economic Belt exhibit an inverted “U”-shaped pattern, rising initially and then declining, while carbon emission intensity continues to decrease. In terms of emission sources, methane emissions from paddy fields account for the highest proportion, emissions from agricultural inputs show a steady decline, and emissions from soil use continue to rise. Regarding driving factors, crop farming efficiency is the most significant negative driver, while regional economic development serves as the primary positive driver; the decoupling pattern has gradually transitioned from “weak decoupling” to a predominantly “strong decoupling” pattern; projection results indicate that both carbon emissions and emission intensity from crop farming in the Yangtze River Economic Belt will generally decline in the future, though regional pressure for emission reductions remains significant; agricultural industrial structures should be optimized and adjusted, with efforts focused on promoting the standardized and scaled development of organic and ecological agriculture to facilitate the green and low-carbon transformation of agriculture.

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