Exploring the impact mechanism of low-carbon multivariate coupling system in Chinese typical cities based on machine learning

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.

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“…Boudhan et al (2019) explored the comparative dynamics and internal mechanisms of dust under both dry and humid conditions, and inferred a correlation between humidity and dust. Yang et al (2023) utilized random forest algorithms and coupled coordination degree models to study the impact mechanisms of multicoupling systems, thereby establishing a basis for verifying correlations among weather-related factors. Rad et al (2022) also evaluated the direct interplay between air pollution and environmental parameters via machine learning methodologies, and examined temperature, humidity, light intensity, dust concentration, and some gas changes.…”