中国旅游业碳排放的影响因素分解及脱钩效应

采用广义迪氏指数分解法（GDIM）分解2000~2017年中国旅游业碳排放的影响因素，并在此基础上采用Tapio脱钩因果链模型分析旅游业碳排放的脱钩效应.结果表明：旅游业增加值、旅游业能源消耗量和旅客人次数是旅游业碳排放的促增因素，增加值能源强度和人均旅游业增加值是旅游业碳排放的促降因素，增加值碳强度、能源消耗碳强度和人均旅游业碳排放对旅游业碳排放的促增和促降作用在研究期间均有出现；旅游业能源消耗量的累积促增效应最大，为2030.13万t，增加值能源强度的累积促降效应最大，为103.29万t；旅游业碳排放的脱钩状态不佳，但近年来有所改善；人均脱钩弹性波动剧烈，节能弹性的变化是其波动的主要原因.

Factor decomposition and decoupling effect of Chinese tourism-derived carbon emissions

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.