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

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬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.

第四次技術革命と「デュアルカーボン」戦略目標に牽引され、人工知能は都市のグリーンで低炭素な発展に新たな道を切り開いた。両者の因果関係を探ることは、中国経済の持続可能な転換にとって重要な意義を持つ。2011年から2021年までの人工知能発展度が比較的高い長江経済帯の都市パネルデータを研究サンプルとし、双方向固定効果、二重機械学習、空間ダービンなどの複数のモデルを採用して、人工知能が都市のグリーンで低炭素な発展において果たす促進的役割を調査した。その結果、人工知能は都市経済に対して顕著な資源節約効果と環境排出削減効果を持っていることが明らかになった。この結論は一連の頑健性テスト後も依然として成立する。人工知能は主に技術革新と産業構造の高度化を通じて資源節約と環境排出削減を実現している。さらに、教育水準と市場統合度は、人工知能が都市のグリーンで低炭素な発展を促進する過程において正の調整効果を持っている。空間分析によると、環境排出削減の面では、人工知能は自地域と周辺地域の環境排出削減の両方に促進効果を持っている。資源節約の面では、人工知能は自地域の資源節約を促進できるが、周辺地域の資源消費強度には明らかな影響を与えない。

AI 翻訳（deepseek-v4-flash）。 正確を期す場合は下の原文を参照してください。

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.

• openalex https://pubmed.ncbi.nlm.nih.gov/42473368first seen 2026-07-22 05:03:36