[Empirical Evidence of Artificial Intelligence Empowering Urban Green and Low-carbon Development： Taking the Yangtze River Economic Belt as an Example].
人工知能が都市のグリーン・低炭素発展を促進する実証的証拠：長江経済ベルトを例として (AI 翻訳)
Weixiang Xu, Yi-Fan Shi, Jinhui Zheng
🤖 gxceed AI 要約
日本語
本研究は、2011年から2021年までの長江経済ベルトの都市パネルデータを用い、AIが都市のグリーン・低炭素発展に与える影響を実証分析した。二重機械学習や空間ダービンモデルにより、AIが資源節約と環境排出削減を促進し、その経路として技術革新と産業構造高度化を特定した。教育水準と市場統合が正の調整効果を持つことも明らかにした。
English
This study uses panel data from cities in the Yangtze River Economic Belt (2011-2021) to empirically analyze AI's impact on urban green and low-carbon development. Applying dual machine learning and spatial Durbin models, it finds that AI promotes resource conservation and environmental emission reduction through technological innovation and industrial structure upgrading. Education level and market integration positively moderate this effect.
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
本論文は中国の事例であるが、日本のGX政策（特に都市の脱炭素化やAI活用）にも示唆を与える。日本ではSSBJや有報におけるDX・GX連携が注目される中、AIによる資源効率向上と排出削減の実証結果は、企業・自治体の取り組みの参考となる。
In the global GX context
This paper contributes to the global literature on AI-driven green development, offering empirical evidence from China. It aligns with international frameworks like TCFD and ISSB that encourage technological innovation for climate goals. The mechanisms identified (innovation and industrial upgrading) are relevant for cities worldwide.
👥 読者別の含意
🔬研究者:Provides rigorous empirical evidence on AI's causal impact on urban green development, with insights on mechanisms and spatial spillovers.
🏢実務担当者:Urban planners and sustainability officers can leverage AI for resource efficiency and emission reductions, supported by moderating factors like education and market integration.
🏛政策担当者:Highlights the importance of supporting AI innovation, industrial upgrading, and market integration to enhance green and low-carbon outcomes.
📄 Abstract（原文）
Driven by the Fourth Technological Revolution and the "dual carbon" strategic goals， artificial intelligence has opened up new paths for the green and low-carbon development of cities. Exploring the causal relationship between the two is of great significance for the sustainable transformation of China's economy. Taking the urban panel data of the Yangtze River Economic Belt with a relatively high degree of artificial intelligence development from 2011 to 2021 as the research sample， multiple models such as bidirectional fixed effects， dual machine learning， and spatial Dubin were adopted to investigate the enabling role of artificial intelligence in the green and low-carbon development of cities. It was found that artificial intelligence had a significant resource-saving effect and environmental emission reduction effect on urban economy. This conclusion still held true after a series of robustness tests. Artificial intelligence mainly achieved resource conservation and environmental emission reduction through technological innovation and industrial structure upgrading. Moreover， the educational level and the degree of market integration had a positive moderating effect in the process of artificial intelligence empowering the green and low-carbon development of cities. Spatial analysis showed that in terms of environmental emission reduction， artificial intelligence had a promoting effect on both local and neighboring environmental emission reduction. In terms of resource conservation， artificial intelligence can promote local resource conservation but has no obvious impact on the resource consumption intensity of neighboring areas.
🔗 Provenance — このレコードを発見したソース
- openalex https://pubmed.ncbi.nlm.nih.gov/42473368first seen 2026-07-22 05:03:36
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