Decoupling and decomposition analysis of carbon emissions in Beijing's tourism traffic

被引:27
作者
Ma, Huiqiang [1 ]
Liu, Jiale [1 ]
Xi, Jianchao [2 ]
机构
[1] Shanxi Univ Finance & Econ, Coll Culture & Tourism, Taiyuan 030006, Shanxi, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Resources, Key Lab Land Surface Patterns & Modeling, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
Tourism traffic; Carbon emissions; Tapio model; LMDI approach; Green and low-carbon tourism; Energy conservation; CO2; EMISSIONS; ENERGY-CONSUMPTION; ECONOMIC-GROWTH; SECTOR; CHINA; INTENSITY; IMPACTS; TECHNOLOGY; PATTERNS; DRIVERS;
D O I
10.1007/s10668-021-01657-w
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Using the calculation method of the United Nations World Tourism Organization (UNWTO), this paper measured the carbon emissions of tourism traffic and their evolution process in Beijing from 2005 to 2017. The Tapio model and Logarithm Mean Divisia Index (LMDI) approach were used to discuss the decoupling relationship between economic development and the change of tourism traffic carbon emissions and the influencing factors. There are six major indicators in our analysis, including (1) tourists scale, (2) per capita tourism consumption level, (3) contribution rate of tourism industry to Gross Domestic Product (GDP), (4) passenger traffic volume per unit GDP, (5) energy consumption per unit passenger traffic volume, and (6) energy structure. The results showed that: the main positive drivers are tourists scale, per capita tourism consumption level and energy consumption per unit of passenger traffic volume. In addition, per unit GDP passenger traffic volume is an effective factor to restrain the growth of carbon emissions. And the economic development of Beijing is developing in step with the change of carbon emissions in Beijing's tourism traffic. The research results have important theoretical and practical significance for Beijing to formulate emission reduction policies and develop low-carbon economy.
引用
收藏
页码:5258 / 5274
页数:17
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