Affiliations: Tourism College of Zhejiang, Hangzhou, Zhejiang, China | E-mail: [email protected]
Correspondence:
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Corresponding author: Tourism College of Zhejiang, Hangzhou, Zhejiang, China. E-mail: [email protected].
Abstract: Tourism has had some negative effects while generating positive results. The carbon emissions produced by tourism, which is not a “smokeless industry” in traditional cognition, account for a certain proportion of the global greenhouse gas emissions. Tourism transportation, tourist accommodation, and other tourism activities all contribute to the carbon emission of tourism, and various tourism activities not only stimulate the economy but also increase air pollution. As a big industry, tourism’s growth and development have continuously increased energy consumption, and the pressure on energy conservation and emission reduction has also been greatly aggravated. In this study, the tourism carbon emissions in each province of China were estimated using a “top-down” calculation model, the tourism energy consumption factors were decomposed using a logarithmic mean Divisia index model, and the driving factors of tourism carbon emissions were analyzed through a panel data model. Results show that the tourism carbon emissions in China rapidly increased from 360.74 million tons in 2006 to 853.28 million tons in 2021. The driving factors of tourism energy consumption in China are economic development, energy efficiency, and population, while the inhibiting factors are tourism intensity and energy structure. The per capita GDP, the proportion of the tertiary industry, the turnover of tourists, and the level of urbanization all significantly promote the growth of tourism carbon emissions in China at 1%. The research results are of great significance to the proposal of measures for tourism carbon emission reduction in combination with the situation of various provinces and cities, promoting regional economic development and boosting the development of tourism in China under the background of a low-carbon economy.
Keywords: LMDI, panel data model, tourism, energy consumption, carbon emissions, driving factors
