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2000〜2021年中国における土地利用由来炭素排出の時空間的特徴の変遷と炭素排出予測

[Spatial-temporal Characteristics Evolution of Land Use Carbon Emissions in China from 2000 to 2021 and Carbon Emission Prediction]. (原題)

Jia-Wei Yu, Zu-Heng Cheng, De-Xing An, Wen-Lin Zhang, Yu-Fen Niu, Jun Tong

PubMedジャーナル2026-09-08#気候科学Origin: CN対象セクター: cross_sector
DOI: 10.13227/j.hjkx.202501138
原典: https://pubmed.ncbi.nlm.nih.gov/42765214

🤖 gxceed AI 要約

日本語

中国の2000〜2021年の土地利用変化に伴う炭素排出・吸収を、衛星NPPデータと社会経済統計から推計した研究。建設用地の拡大で排出は235%増、森林吸収は16.6%増。GPRモデルで2028年ピーク・2060年以前のカーボンニュートラルを予測し、地域間格差と脱カップリングの段階的変化を示した。

English

Using land-use, socioeconomic, and MODIS NPP data, this study estimates China's land-use carbon emissions and sequestration for 2000–2021. Construction-land emissions rose 235% while forest sequestration grew 16.6%. A Gaussian Process Regression model projects a 2028 emissions peak and carbon neutrality before 2060, with marked regional disparities and shifting decoupling states.

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

中国の土地利用規制・炭素吸収源政策の実証的裏付けであり、日本のSSBJ・有報でのScope3土地利用・森林クレジット評価や、自治体の脱炭素計画策定に示唆を与える。地域間格差と生態補償の議論は、日本の地域脱炭素・カーボンオフセット制度設計にも参考になる。

In the global GX context

Provides empirical evidence on land-use emissions and sinks relevant to national inventory and net-zero pathway design, complementing TCFD/ISSB disclosure on land-use and removals. The regional Gini and decoupling analysis offers a template for subnational climate policy and ecological compensation debates globally.

👥 読者別の含意

🔬研究者:土地利用由来排出の長期推計とGPR予測手法、地域間格差の定量化に関心のある研究者に有用。

🏢実務担当者:森林・土地利用クレジットやScope3土地利用排出の評価、地域カーボンオフセット戦略の検討に活用可能。

🏛政策担当者:地域別の排出ピーク時期と生態補償・炭素吸収源政策の設計、脱カップリング政策の評価に示唆。

📄 Abstract(原文)

The spatiotemporal evolution of carbon emissions and its future trend prediction, as an important scientific issue in response to global climate change, has become a key area of research in climate science, environmental science, and policy studies. As the world's largest emitter of carbon, China's land use changes have had a profound impact on the dynamic changes in carbon emissions. This study utilizes the annual land use dataset from Wuhan University, socioeconomic data from the China Statistical Yearbook, and MODIS global net primary productivity (NPP) data to examine the carbon emissions and carbon sequestration from various 3land types such as urban areas, arable land, and forest land in different regions. It systematically analyzes the specific impact of land use changes in China on carbon emissions from 2000 to 2021. Additionally, the study employs a Gaussian Process Regression (GPR) model for carbon emission forecasting and analyzes the spatial distribution of carbon emissions in relation to economic development using the Gini coefficient and the TAPIO decoupling model. The results indicate that: ① From 2000 to 2021, construction land expanded by 67.28% (2000-2021), with an average annual growth rate exceeding 4%. Significant conversion of arable land occurred in the eastern region. Forest land/water body areas increased by 2.12% and 10.38%, respectively, with notable ecological restoration in the western region. Grassland, arable land, and unused land decreased by 1.86%-3.28%, showing clear characteristics of intensive land use. ② From 2000 to 2021, carbon emissions from construction land dominated in proportion, with total emissions increasing by 235% (an annual growth rate of 6.07%) and spatial diffusion extending to the central and western regions. Forest carbon sequestration increased by 16.6% (an annual growth rate of 0.77%), while carbon absorption by grasslands slightly declined, and the carbon function differentiation between the eastern and western regions intensified. ③ The carbon emission Gini coefficient decreased from 0.592 2 in 2000 to 0.540 7 in 2021, indicating a more even distribution of carbon emissions. The carbon emissions of the top 10% grids increased from 108.9 million tons to 330.4 million tons, showing that high-emission areas were still driving the growth of carbon emissions. The internal differences in the western region were the largest (Gini coefficient of 0.847 3). ④ From 2000 to 2013, China was in a "weak decoupling" state, with economic growth accompanied by an increase in carbon emissions. From 2014 to 2016, China entered a "strong decoupling" phase, where GDP growth occurred alongside a reduction in carbon emissions. From 2017 onwards, carbon emissions began to rise again, returning to a "weak decoupling" state. ⑤ The GPR model predicted that China's carbon emissions will peak in 2028, and carbon neutrality will be achieved before 2060. The western region has already become a carbon sink, while the central and eastern regions will reach their peak around 2027. The potential for carbon neutrality in regions like Tibet, Qinghai, and Inner Mongolia is significant, while heavy industrial provinces such as Shandong, Liaoning, and others face notable pressure, requiring collaborative solutions of carbon-negative technologies and ecological compensation.

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