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グリーン低炭素循環発展の時空間パターンとシステム結合調和度評価：中国貴州省9市の事例研究

Spatiotemporal pattern and system coupling coordination evaluation of green low-carbon circular development: A case study of nine cities in Guizhou province, China (原題)

Guihui Lu, Shan Zhenpei, Baoquan Ning, Meilan Yang, Yanpo Yang

Cities📚 査読済 / ジャーナル2026-10-20#エネルギー転換Origin: CN
DOI: 10.1016/j.cities.2026.107702
原典: https://doi.org/10.1016/j.cities.2026.107702

🤖 gxceed AI 要約

日本語

貴州省の9市を対象に、2013〜2022年のグリーン低炭素循環発展（GLCD）をCRITIC-G1-灰色相関TOPSISで評価した研究。カルスト地形に即した地域指標を組み込み、カーネル密度推定と改良型結合調和度モデルで4サブシステム間の相互作用を分析する。GLCDは変動しつつ上昇し2019年に0.7763でピーク、低炭素が最も高く循環発展が最も弱い。貴陽が最高、畢節が最低で中心–周辺の格差があり、結合強度は高いが調和度は平均0.6055にとどまる。

English

This study evaluates green low-carbon circular development (GLCD) across nine prefecture-level cities in Guizhou, China, from 2013 to 2022 using a CRITIC-G1-grey relational TOPSIS framework with karst-specific indicators. Kernel density estimation and an improved coupling coordination model reveal a fluctuating upward trend peaking at 0.7763 in 2019, with low-carbon development strongest and circular development persistently weakest. Guiyang ranks highest and Bijie lowest, showing a center-periphery gradient; coupling intensity is high but coordination averages only 0.6055.

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

中国地方省レベルの統合評価指標の設計例として、日本の自治体GX計画や地域脱炭素評価の指標設計を検討する際の比較材料になりうる。ただしSSBJや有報開示との直接の接続はない。

In the global GX context

Offers a methodological template for subnational integrated assessment of green, low-carbon, and circular development, relevant to regional transition benchmarking. It sits outside corporate disclosure frameworks (TCFD/ISSB/CSRD) but informs how local governments might measure transition progress.

👥 読者別の含意

🔬研究者:サブナショナル規模での多基準評価と結合調和度モデルの応用例として、指標設計や時空間分析の手法を参照できる。

🏢実務担当者:地域拠点の立地評価や自治体との連携時に、地域のグリーン・低炭素・循環の進展度を把握する参考になる。

🏛政策担当者:省内格差の是正と循環資源利用の強化、サブシステム間調和の向上が地域GX政策の優先課題であることを示す。

📄 Abstract（原文）

Green low-carbon circular development (GLCD) provides an integrated perspective for reconciling environmental protection, carbon mitigation, resource efficiency, and economic development, yet its spatiotemporal heterogeneity and internal coordination remain insufficiently understood at the intra-provincial scale. This study develops an Integrated Spatiotemporal CRITIC-G1-Grey Relational TOPSIS (IS-CG-GRTOPSIS) framework, incorporating region-specific indicators to reflect the ecological and resource characteristics of Guizhou's karst environment, to evaluate GLCD across nine prefecture-level administrative units in Guizhou Province from 2013 to 2022. Kernel density estimation is further employed to examine the evolution of the spatial distribution, while an Improved Coupling Coordination Degree Model (ICCDM) is used to characterize interactions and coordination among the green, low-carbon, circular, and economic development subsystems. The results show that GLCD exhibited an overall fluctuating upward trajectory, reaching a peak of 0.7763 in 2019 before declining and subsequently recovering. Among the four subsystems, low-carbon development achieved the highest level, followed by green, economic, and circular development, with circular development remaining the most persistent weakness. Substantial spatial disparities were observed: Guiyang consistently exhibited the highest GLCD level, whereas Bijie remained at the lowest level, with a center–periphery gradient associated with the concentration of economic, technological, and policy resources. Although the four subsystems displayed relatively high coupling intensity, their coordination remained comparatively limited, with a mean coordination degree of 0.6055. Weak economic and circular development, together with insufficient low-carbon–circular coordination, constrained systemic coordination. These findings highlight the need to strengthen circular resource use, reduce intra-provincial disparities, and enhance cross-subsystem coordination in regional green transformation.

🔗 Provenance — このレコードを発見したソース

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