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Decoupling and decomposition analysis of carbon emissions in Beijing’s tourism traffic
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 decou...
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Published in: | Environment, development and sustainability development and sustainability, 2022-04, Vol.24 (4), p.5258-5274 |
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description | 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. |
doi_str_mv | 10.1007/s10668-021-01657-w |
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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.</description><identifier>ISSN: 1387-585X</identifier><identifier>EISSN: 1573-2975</identifier><identifier>DOI: 10.1007/s10668-021-01657-w</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Carbon ; Change agents ; Decoupling ; Earth and Environmental Science ; Ecology ; Economic development ; Economic Geology ; Economic Growth ; Economics ; Emission measurements ; Emissions ; Emissions control ; Energy consumption ; Environment ; Environmental Economics ; Environmental Management ; GDP ; Gross Domestic Product ; Passengers ; Sustainable Development ; Tourism ; Tourists ; Traffic ; Traffic volume</subject><ispartof>Environment, development and sustainability, 2022-04, Vol.24 (4), p.5258-5274</ispartof><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021</rights><rights>The Author(s), under exclusive licence to Springer Nature B.V. 2021.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-618b33e38269e561cf7c237a20bea11cb79af3a4cb78608677c7818ad40517d3</citedby><cites>FETCH-LOGICAL-c319t-618b33e38269e561cf7c237a20bea11cb79af3a4cb78608677c7818ad40517d3</cites><orcidid>0000-0002-7284-1234</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2640668963/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2640668963?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,11687,12846,27923,27924,33222,36059,44362,74666</link.rule.ids></links><search><creatorcontrib>Ma, Huiqiang</creatorcontrib><creatorcontrib>Liu, Jiale</creatorcontrib><creatorcontrib>Xi, Jianchao</creatorcontrib><title>Decoupling and decomposition analysis of carbon emissions in Beijing’s tourism traffic</title><title>Environment, development and sustainability</title><addtitle>Environ Dev Sustain</addtitle><description>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. 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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. 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subjects | Carbon Change agents Decoupling Earth and Environmental Science Ecology Economic development Economic Geology Economic Growth Economics Emission measurements Emissions Emissions control Energy consumption Environment Environmental Economics Environmental Management GDP Gross Domestic Product Passengers Sustainable Development Tourism Tourists Traffic Traffic volume |
title | Decoupling and decomposition analysis of carbon emissions in Beijing’s tourism traffic |
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