DocumentCode :
3446580
Title :
Tourism CO2 emissions measure and temporal and spatial differences study — A case of Henan Province in China
Author :
Xu Li ; Hongxia Sun ; Yaochen Qin
Author_Institution :
Key Lab. of Geospatial Technol. for the Middle & Lower Yellow River Regions, Kaifeng, China
fYear :
2013
fDate :
20-22 June 2013
Firstpage :
1
Lastpage :
6
Abstract :
In recent years, the tourism industry CO2 emissions measures become a hot topic of academic research. The tourism carbon emissions´ research is relatively mature in foreign scholars, but domestic scholars are lagging far behind, which is largely subject to our imperfect tourism statistical system. This paper discusses the tourism CO2 emissions measure based on the statistical coverage of China´s tourism, and applied to a relatively well-developed tourism industry in Henan Province, and calculates the CO2 emissions of Henan Province tourism sector, and last analysis the spatial and temporal differences of the Henan Province. Concluded that Henan Province tourism CO2 emissions are rapidly increasing, the intensity of tourism CO2 emissions is gradually declined, the CO2 emissions´ disparity of three sectors of tourism is gradually narrowing, the tourism CO2 emissions of city in Henan Province is quietly different, and so on. Lastly we make several recommendations for tourism energy saving that provide a scientific basis for low-tourism´s development of Henan Province.
Keywords :
air pollution; travel industry; CO2; China tourism; Henan Province tourism sector; domestic scholars; foreign scholars; tourism carbon emission research; tourism energy saving; tourism industry carbon dioxide emissions; tourism sector disparity; tourism statistical system; Carbon dioxide; Cities and towns; Entertainment industry; Market research; Rail transportation; Road transportation; CO2 emission; spatial and temporal differences; tourism;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
Conference_Location :
Kaifeng
ISSN :
2161-024X
Type :
conf
DOI :
10.1109/Geoinformatics.2013.6626140
Filename :
6626140
Link To Document :
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