中国デュアルカーボン目標下における山東省の汚染・炭素削減シナジーの時空間的進化、地域格差、駆動要因
Spatiotemporal Evolution, Regional Disparities, and Driving Factors of Synergistic Pollution and Carbon Reduction in Shandong Province Under China’s Dual-Carbon Targets (原題)
Wenqing Zhang, Zikun Yan, Guihuan Yan, Chongqing Xu
🤖 gxceed AI 要約
日本語
中国デュアルカーボン戦略の下、山東省16市の2010〜2023年パネルデータを用い、汚染・炭素削減の結合協調度、地域格差、駆動要因を分析した。結合協調度は0.760から0.847へ上昇したが、その改善はほぼ汚染削減のみに起因し、炭素削減指数は6.6%低下する「汚染急減・炭素停滞」の非対称性が生じている。格差は東西勾配ではなく都市単位で分化し、エネルギー強度と第二次産業比率が最も頑健な駆動要因であった。
English
Using 2010–2023 panel data from 16 Shandong cities, this study analyzes coupling coordination, regional disparities, and drivers of synergistic pollution and carbon reduction under China's Dual-Carbon strategy. Coordination rose from 0.760 to 0.847, but driven almost entirely by pollution reduction, while the carbon reduction index fell 6.6%, revealing a 'rapid pollution reduction, stagnant carbon reduction' asymmetry. Disparities are city-level rather than east–west, with energy intensity and secondary industry share the most robust drivers.
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
中国の地方省レベルでの炭素削減停滞は、日本のSSBJ・有報でのScope1/2削減目標管理や地域別脱炭素政策を考える上で比較材料となる。特に「汚染削減は進むが炭素削減が停滞する」構造は、日本企業の工場立地・サプライチェーン脱炭素戦略における中国拠点リスク評価に示唆を与える。
In the global GX context
This paper adds subnational empirical evidence to the global decarbonization literature, showing that pollution co-benefits can mask stalled carbon reduction—a caution for ISSB/CSRD disclosure that treats environmental performance as monolithic. It also highlights city-level heterogeneity relevant to transition finance allocation in emerging economies.
👥 読者別の含意
🔬研究者:中国地方省の汚染・炭素シナジー評価手法（結合協調度＋Dagumジニ＋固定効果）の応用例として参考になる。
🏢実務担当者:中国拠点を持つ企業は、汚染規制対応が炭素削減を伴わない可能性を踏まえ、拠点別の炭素リスクを再評価すべき。
🏛政策担当者:地域別脱炭素政策では、汚染削減指標だけでなく炭素削減指標を分離してモニタリングする必要性を示唆。
📄 Abstract（原文）
Synergistic pollution and carbon reduction is central to China’s Dual-Carbon strategy, yet the structural constraints on its regional evolution remain insufficiently examined. Using panel data from 16 prefecture-level cities in Shandong Province over 2010–2023, this study combines a coupling coordination degree model, Dagum Gini coefficient decomposition, and a panel fixed-effects model. Three findings emerge. First, the coupling coordination degree rose from 0.760 to 0.847, but this improvement was driven almost entirely by pollution reduction. The pollution reduction composite index increased by 31.7%, whereas the carbon reduction composite index declined by 6.6%, producing a pronounced “rapid pollution reduction, stagnant carbon reduction” asymmetry. Second, the spatial pattern was characterized by city-level differentiation rather than an east–west gradient, with Binzhou and Rizhao lagging persistently. Third, the Dagum Gini coefficient declined from 0.088 to 0.068, with transvariation intensity remaining the dominant source of disparity throughout the period (contributing 40.6–63.6%), indicating the limited explanatory power of the circle-based classification. Energy intensity and secondary industry share were the most robust drivers, whereas R&D intensity was statistically indistinguishable from zero. Policy should therefore prioritize energy efficiency improvement and city-specific targeting of persistently lagging cities.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.3390/su182010408first seen 2026-10-16 05:03:42
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