基于随机森林模型的我国县域碳排放强度格局与影响因素演进分析

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Abstract To explore the spatial distribution pattern of the county-level carbon emission intensity and the dynamic change in influencing factors, in this paper, ArcGIS spatial statistical model was adopted to measure and analyze the spatial distribution pattern of the carbon emission intensity from 2009 to 2017. Then key influencing factors and their effects change were identified by the random forest model. As results indicated, the average county-level carbon emission intensity fluctuated and decreased from 2009 to 2017. The county-level average carbon emission intensity was 2.02t/10000 yuan in 2017, indicating a significant potential in carbon emission reduction at county-level. Besides, there was significant and rising spatial autocorrelation in carbon emission intensity, but the spatial correlation varied between north-south and east-west regions. The hot-spot area of carbon emission intensity expanded westward, while the cold-spot area expended both southward and northward. Among the key influencing factors, distance to provincial capital, industrial structure, road network density and population played more important role compared with economic development, fiscal revenue and expenditure, number of green patents and high-speed railway. Green patent, total population, and economic development risen in the importance rankings over time, while industrial structure and population density fallen back in the rankings. In addition, most of factors were non-linear correlated with the county-level carbon emission intensity.

Key words： county-level carbon emission intensity spatial pattern random forest model influencing factors

Received: 22 November 2021

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	YU Wen-meng
	ZHANG Ting-ting
	SHEN Da-jun

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YU Wen-meng,ZHANG Ting-ting,SHEN Da-jun. County-levelspatial pattern and influencing factors evolution of carbon emission intensity in China:A random forest model analysis[J]. CHINA ENVIRONMENTAL SCIENCECE, 2022, 42(6): 2788-2798.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2022/V42/I6/2788

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