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- W4328049076 abstract "Abstract Low-carbon city construction is one of the key issues that must be addressed for China to achieve high-quality economic development and meet the Sustainable Development Goals. This study creates a comprehensive evaluation index system of low-carbon city multivariate system based on carbon emission data from 30 typical Chinese cities from 2006 to 2017 and evaluates and analyzes the trend of city low-carbon levels using the CRITIC-TOPSIS technique and MK method. Meanwhile, the influence mechanism of the multi-coupled system is investigated using the coupling coordination degree model and random forest algorithm.The results show that there are 8 cities with a significant increasing trend of low-carbon level, 19 cities with no significant monotonic change trend, and 3 cities with a decreasing trend of low-carbon level. By analyzing the coupling coordination degree, we found that the coupling coordination degree between low-carbon level and economic development in most cities tends to increase year by year, from the initial antagonistic effect to a good coordination development trend, which confirms the “inverted U-shaped” relationship between economy and carbon emission. In addition, industrial pollutant emissions, foreign direct investment, and economic output are the core drivers of low-carbon levels in cities." @default.
- W4328049076 created "2023-03-22" @default.
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- W4328049076 date "2023-03-20" @default.
- W4328049076 modified "2023-09-30" @default.
- W4328049076 title "Exploring the impact mechanism of low-carbon multivariate coupling system in Chinese typical cities based on machine learning" @default.
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- W4328049076 doi "https://doi.org/10.1038/s41598-023-31590-z" @default.
- W4328049076 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36941319" @default.
- W4328049076 hasPublicationYear "2023" @default.
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