黄河流域都市群における土地利用炭素排出効率の空間ネットワーク構造特性の分析
[Analysis of the Spatial Network Structural Characteristics of Land Use Carbon Emission Efficiency in Urban Agglomerations in the Yellow River Basin]. (原題)
Chang Lu, Qin-Lin Guo, Zhi-Yu Wang, Jian Shang, Feng Zhang, Yu-Lei Gong
🤖 gxceed AI 要約
日本語
黄河流域の都市群を対象に、土地利用炭素排出効率の空間ネットワーク構造を超効率SBMモデルと社会ネットワーク分析で解明。効率は向上したが地域格差が拡大し、中心都市（青島、東営、鄭州など）のハブ性が強化。地理的距離や経済発展、気温、炭素排出強度、建設用地が空間的相関に影響。
English
This study analyzes the spatial network structure of land use carbon emission efficiency in urban agglomerations of the Yellow River Basin using super-efficiency SBM and social network analysis. Efficiency improved but spatial disparities widened, with core cities like Qingdao, Dongying, and Zhengzhou becoming key nodes. Factors such as geographical distance, economic development, temperature, carbon intensity, and construction land significantly influence spatial correlations.
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
中国の地域戦略に基づく研究で、日本では国土計画や都市政策への示唆が得られる。日本の自治体や都市圏での土地利用と炭素排出の関係を分析する際の方法論的参考になる。
In the global GX context
This study contributes to global scholarship on spatial carbon efficiency and urban agglomerations, offering methods applicable to regional decarbonization planning. It highlights the role of network structures and spillover effects, relevant for climate policy in rapidly urbanizing regions.
👥 読者別の含意
🔬研究者:土地利用と炭素効率の空間ネットワーク分析手法を学ぶ価値がある。
🏢実務担当者:都市計画や地域脱炭素戦略の立案に参考になる。
🏛政策担当者:地域間連携や中心都市の役割を考慮した政策設計に示唆を与える。
📄 Abstract（原文）
Under the national strategy for ecological conservation and high-quality development in the Yellow River Basin， this study investigates the spatial correlation patterns and formation mechanisms of land use carbon emission efficiency in urban agglomerations. Utilizing the super-efficiency SBM model with undesirable outputs and social network analysis， we examine the structural characteristics of the carbon emission efficiency network and identify core cities within the network. The key findings are as follows： ①During the study period， land use carbon emission efficiency in the Yellow River Basin urban agglomerations significantly improved， with spatial disparities gradually widening. High-efficiency zones concentrated in the eastern and central regions. ②Spatial correlations among urban agglomerations notably strengthened， with the Guanzhong Plain Urban Agglomeration， Shandong Peninsula Urban Agglomeration， Jiziwan Metropolitan Area， and Central Plains Urban Agglomeration demonstrating significant spatial spillover effects. ③The overall network exhibited stable and balanced characteristics. Analysis of individual network features revealed substantially enhanced centrality in cities such as Qingdao， Dongying， and Zhengzhou， establishing them as key network nodes. ④Urban agglomerations were categorized into four functional plates： net spillover， main beneficiary， broker， and net beneficiary. ⑤Geographical distance， economic development level， mean temperature， carbon emission intensity， and construction land exerted significant impacts on the spatial correlation of land use carbon emission efficiency.
🔗 Provenance — このレコードを発見したソース
- openalex https://pubmed.ncbi.nlm.nih.gov/42670098first seen 2026-09-03 05:13:59
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