[Spatiotemporal Dynamics， Decoupling Analysis， and Driving Mechanisms of Carbon Emissions from China's Livestock Sector].
中国畜産部門からの炭素排出の時空間動態、デカップリング分析、および駆動メカニズム (AI 翻訳)
Nan Zhang, Jing Tang, Junyi Yang, Yong-Ji Luan, Shu-Hang He, Xiao Guan, Yan-Jun Chen
🤖 gxceed AI 要約
日本語
本論文は、2001～2022年の中国31省の家畜データを用いてIPCC排出係数法により炭素排出量を推計。カーネル密度推定、Tapioデカップリングモデル、LMDI分解法により時空間パターンと経済とのデカップリング、要因を分析した。結果、排出総量は「増加-減少-回復」の変動を示し、西部に高排出濃度、経済効果が排出増加の主要因、強度効果は第14次五カ年計画で排出削減に寄与した。
English
This study estimates carbon emissions from China's livestock sector (2001-2022) using IPCC methodology and spatial-temporal analysis. It finds fluctuating total emissions with high concentration in central and southwestern regions, weak decoupling from economic growth except 2006-2010, and that economic effect drives increases while intensity effect recently contributed to reductions.
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
中国畜産部門の排出実態と削減要因を詳細に分析しており、日本の畜産業における温室効果ガスインベントリ改善や地域別排出削減策の検討に参考となる。特にLMDI分解手法は日本の都道府県別分析にも応用可能。
In the global GX context
This paper provides a comprehensive empirical analysis of livestock carbon emissions in China, a major agricultural GHG source. Its use of decoupling and decomposition methods contributes to global understanding of agricultural emission drivers and mitigation potential, relevant for national inventory reporting under UNFCCC.
👥 読者別の含意
🔬研究者:Offers a rigorous methodology combining IPCC emission factors, spatial analysis, and decomposition for agricultural GHG studies.
🏢実務担当者:Provides insights for livestock operations on emission hotspots and reduction levers (intensity effect).
🏛政策担当者:Highlights regional disparities and the need for targeted mitigation policies in the livestock sector.
📄 Abstract（原文）
Against the backdrop of global climate change， the livestock sector， as a major source of agricultural greenhouse gas emissions， plays a critical role in shaping carbon reduction pathways and regulatory mechanisms. Based on slaughter and inventory data of major livestock and poultry species across 31 provinces （autonomous regions and municipalities） in China from 2001 to 2022， carbon emissions were estimated using the Intergovernmental Panel on Climate Change （IPCC） emission coefficient method. Kernel density estimation， the Tapio decoupling model， and the logarithmic mean Divisia index （LMDI） decomposition method were employed to systematically analyze the spatiotemporal patterns， economic decoupling status， and driving mechanisms of livestock carbon emissions. The results show that： ① Total emissions exhibited a fluctuating trend of "increase-decline-rebound，" with spatial patterns characterized by "lower in the east and higher in the west，" and high-emission concentration in central and southwestern regions， while emission intensity remained high in the northwestern pastoral areas. ② Strong decoupling occurred only from 2006 to 2010， with most other periods showing weak decoupling， and notable regional differences. ③ Economic effect consistently served as the primary driver of emission growth， while the intensity effect shifted from positive to negative and significantly contributed to emission reduction during the 14th Five-Year Plan period. Structural and population effects had a relatively limited impact. These findings indicate that livestock carbon emissions in China exhibit significant regional disparities， emerging technological mitigation effects， and a strong influence of economic growth.
🔗 Provenance — このレコードを発見したソース
- openalex https://pubmed.ncbi.nlm.nih.gov/42473366first seen 2026-07-22 05:24:15
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