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中国の都市レベルCO2排出の空間構造と不均一な駆動要因：地理的加重時空間分解法からの洞察

Spatial structure and heterogeneous drivers of city-level CO2 emission in China: Insights from geographically weighted spatiotemporal decomposition method (原題)

Yue Wang, Huijie Wen, Peipei Qiu, Xuesong Wang, Wenbo Xue, Yixuan Zheng, Gang Yan, Yuanhang Zhang

Environment Development and Sustainability📚 査読済 / ジャーナル2026-10-17#政策Origin: CN
DOI: 10.1007/s10668-026-08232-1
原典: https://doi.org/10.1007/s10668-026-08232-1

🤖 gxceed AI 要約

日本語

中国337都市の1990〜2020年の人為CO2排出に地理的加重回転経験直交関数（GWREOF）を適用し、20の連続した空間モードを抽出して20の炭素排出管理区を画定した。各区の排出量・炭素収支能力・経済産出・エネルギー強度の格差を分析し、8類型に分類。類型ごとに優先策（エネルギー脱炭素化、石炭規制、生態修復、グリーン製造、熱供給・産業の石炭構造改善、森林吸収源の補償金化など）が異なることを示した。

English

Applying a geographically weighted rotation EOF method to anthropogenic CO2 emissions across 337 Chinese cities (1990–2020), the study identifies 20 contiguous spatial modes and delineates 20 carbon emission management zones. It compares emissions, carbon balance capacity, economic output and energy intensity across zones, classifying them into eight types. Each type carries distinct mitigation priorities, from energy decarbonization to coal controls, green manufacturing and monetizing forest sinks.

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

中国の地域別炭素管理区という発想は、日本の自治体・地域脱炭素（地域循環共生圏や自治体SDGs）やSSBJ開示の地域別リスク評価を考える上で参照枠になる。ただし中国国内の政策設計が主眼で、日本企業の開示実務への直接の示唆は限定的。

In the global GX context

This offers a methodological template for spatially differentiated climate policy design, relevant to jurisdictions implementing regionally tailored decarbonization under national net-zero strategies. It complements global disclosure scholarship by showing how spatial heterogeneity can inform subnational target-setting, though it does not engage TCFD/ISSB frameworks directly.

👥 読者別の含意

🔬研究者:空間的に連続した管理単位を統計手法で画定するアプローチは、地域別排出インベントリや政策評価研究の設計に応用できる。

🏢実務担当者:中国に拠点を持つ企業は、地域別の炭素規制・石炭規制の優先度が異なる点を拠点リスク評価に反映できる。

🏛政策担当者:地域の排出特性と駆動要因に応じた類型別政策の設計が、より効果的な地域脱炭素政策につながることを示す。

📄 Abstract（原文）

Anthropogenic carbon dioxide (CO 2 ) emissions in China have risen persistently, making effective mitigation policies critical for achieving carbon peak and neutrality. Such policies must be regionally tailored, given the large disparities in emission patterns, socioeconomic drivers, and decarbonization potentials across China. Most studies of differentiated emission mitigation concentrate on strategy design but neglect the rationality and accuracy of spatial management units, serving as the spatial objects for policy implementation. The scientific identification of spatial management units is the key to improving the effectiveness of mitigation measures. This study applies the Geographically Weighted Rotation Empirical Orthogonal Function (GWREOF) to anthropogenic CO 2 emissions across 337 Chinese cities from 1990 to 2020, identifying 20 geographically contiguous spatial modes that characterize the spatial structure of China’s CO 2 emissions. These 20 modes are then used to delineate 20 spatially continuous management units for anthropogenic CO 2 emissions (i.e. carbon emission zones). We then analyze the disparities of carbon emission, carbon balance capacity, economic output and energy intensity among different zones and establish the indicator matrix to divide them into eight types. The results show that mitigation priorities differ by zone types: Economically Developed High-Emission Zones and Low-Carbon Sustaining Medium-Emission Zones should prioritize energy decarbonization and low‑carbon tertiary industries. Resource-Dependent High-Emission and Transition-Pressured Medium-Emission Types require stringent coal controls and ecological restoration. Low-Carbon Developing Medium-Emission Type needs green manufacturing upgrades. Energy Optimization Medium-Emission Type should improve coal structures in heating and industry, and Ecologically Prioritized Low-Emission Type should monetize clean energy and forest sinks through compensation. Combining spatially‑based zoning reflecting emission heterogeneity with factor‑based classification reflecting driver heterogeneity, this research improves targeted and systematic governance of anthropogenic CO 2 emissions in China at the national level.

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