Abstract
Traffic carbon emissions have a non-negligible impact on global climate change. Effective estimation and control of carbon emissions from tourism transport will contribute to the reduction in the amount of global carbon emissions. Based on the panel data of Dunhuang in western China from 2010 to 2019, the process analysis method was used to estimate the carbon emissions from tourism traffic of Dunhuang. By establishing the Kaya identity of tourism traffic carbon emissions, the LMDI decomposition method was used to reveal the contribution of different factors to the change in tourism traffic carbon emissions. The results showed that the impact of tourism traffic carbon emissions was diversified; we found three main factors of promoting carbon emissions, namely the number of tourists, tourism expenditure per capita, and energy consumption per unit of passenger turnover. However, the contribution of tourism activities to GDP, passenger turnover per unit of GDP, and energy structure largely inhibited the increase in carbon emissions.
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