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Energy consumption and carbon emission for tourism transport in W orld H eritage S ites: a case of the W ulingyuan area in C hina
Author(s) -
Tang Chengcai,
Zhong Linsheng,
Fan Wenjing,
Cheng Shengkui
Publication year - 2015
Publication title -
natural resources forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.646
H-Index - 49
eISSN - 1477-8947
pISSN - 0165-0203
DOI - 10.1111/1477-8947.12067
Subject(s) - per capita , tourism , energy consumption , consumption (sociology) , carbon fibers , environmental science , agricultural economics , carbon dioxide , environmental engineering , environmental protection , chemistry , geography , engineering , economics , mathematics , population , social science , demography , archaeology , algorithm , sociology , composite number , electrical engineering , organic chemistry
Transport profoundly affects energy use and carbon dioxide emissions in the tourism sector. The W ulingyuan S cenic A rea ( WSA ), a natural heritage destination in C hina, is chosen for the case study. The energy consumption and carbon emission of 10 types of tourism transportation modes at the destination are measured and analyzed using a bottom‐up approach for the period of 1979 to 2010. Scenarios were created to project the effects of single and multiple factors on energy consumption and carbon emission by tourism transportation during 2011‐2020. The results showed the following: (a) there is a large difference in energy consumption and carbon emission per capita and per kilometer per capita among the 10 vehicle modes; (b) the monthly energy consumption and carbon emission of tourism transportation differed significantly, the month with the highest ( O ctober) are respectively 6.8 and 4 times that of the lowest month ( J anuary); (c) the highest annual growth rate of energy consumption and carbon emission are respectively as 32.16% and 27.98% during 1979‐2010; and (d) the amount of energy consumption and carbon emission in the multiple factor scenarios are lower than that in the reference and single factor scenarios during 2011‐2020.