中国旅游业碳排放的影响因素分解及脱钩效应

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Abstract In this study, the Generalized Divisia Index Method (GDIM) was used to decompose the factors influencing China's tourism-derived carbon emissions from 2000 to 2017. On this basis, the Tapio decoupling causal chain model was used to analyze the decoupling effect of tourism-derived carbon emissions. The results show that the added value of tourism, energy consumption of tourism, and number of passengers are factors leading to the increase of tourism-derived carbon emissions. The added value energy intensity and per capita tourism added value are factors leading to the decrease of tourism-derived carbon emissions. The effects of added value carbon intensity, energy consumption carbon intensity, and per capita tourism-derived carbon emissions on tourism-derived carbon emissions are continuously changing. The cumulative increasing effect of energy consumption of tourism is the largest, which is 20.3013million tons, whereas the cumulative decreasing effect of added value energy intensity is the largest, which is 1.0329million tons. The decoupling of tourism-derived carbon emissions is poor, but it has improved in recent years. What's more, the per capita decoupling elasticity fluctuates violently, and the change of energy saving elasticity is the main reason for its fluctuation.

Key words： tourism carbon emission Generalized Divisia Index Method Tapio decoupling causal chain model per capita decoupling elasticity

Received: 06 April 2020

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	SUN Yu-huan
	YANG Guang-chun

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SUN Yu-huan,YANG Guang-chun. Factor decomposition and decoupling effect of Chinese tourism-derived carbon emissions[J]. CHINA ENVIRONMENTAL SCIENCECE, 2020, 40(12): 5531-5539.

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http://www.zghjkx.com.cn/EN/ OR http://www.zghjkx.com.cn/EN/Y2020/V40/I12/5531

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