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Spatial association and identification of carbon neutrality in Chinese tourism, based on social network analysis

Spatial association and identification of carbon neutrality in Chinese tourism, based on social... Achieving tourism carbon neutrality is essential for sustainable tourism development. This paper uses the coupled coordination distance model, modified gravity model and social network analysis to attempt to construct a nationwide tourism carbon neutral spatial network to clarify the role of each province in the process of achieving China’s tourism carbon neutrality. The results show that: (1) only seven provinces will achieve tourism carbon neutrality in the target year of carbon neutrality in China (2060). (2) From 2001 to 2060, most provinces are at the stage of coordinated development of tourism carbon emissions and tourism carbon sinks, but the degree of coordinated development is low. (3) The structure of China’s tourism carbon-neutral spatial network tends to be looser from 2001 to 2060. As the time series progresses, the role of each province in the spatial network will be gradually clarified. (4) In the process of achieving the goal of China’s tourism carbon neutrality, the number of tourism carbon sink input areas is much larger than that of tourism carbon sink output areas. Accordingly, this paper proposes countermeasures from three aspects: government-led, market system and voluntary mechanisms, in order to promote the achievement of China’s tourism carbon neutrality goal. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png All Earth Taylor & Francis

Spatial association and identification of carbon neutrality in Chinese tourism, based on social network analysis

Zhu, Hai; Wang, Liguo
All Earth , Volume 35 (1): 17 – Dec 31, 2023
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17 pages

Spatial association and identification of carbon neutrality in Chinese tourism, based on social network analysis

Abstract

Achieving tourism carbon neutrality is essential for sustainable tourism development. This paper uses the coupled coordination distance model, modified gravity model and social network analysis to attempt to construct a nationwide tourism carbon neutral spatial network to clarify the role of each province in the process of achieving China’s tourism carbon neutrality. The results show that: (1) only seven provinces will achieve tourism carbon neutrality in the target year of carbon...
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Publisher
Taylor & Francis
Copyright
© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
eISSN
2766-9645
DOI
10.1080/27669645.2023.2200632
Publisher site
See Article on Publisher Site

Abstract

Achieving tourism carbon neutrality is essential for sustainable tourism development. This paper uses the coupled coordination distance model, modified gravity model and social network analysis to attempt to construct a nationwide tourism carbon neutral spatial network to clarify the role of each province in the process of achieving China’s tourism carbon neutrality. The results show that: (1) only seven provinces will achieve tourism carbon neutrality in the target year of carbon neutrality in China (2060). (2) From 2001 to 2060, most provinces are at the stage of coordinated development of tourism carbon emissions and tourism carbon sinks, but the degree of coordinated development is low. (3) The structure of China’s tourism carbon-neutral spatial network tends to be looser from 2001 to 2060. As the time series progresses, the role of each province in the spatial network will be gradually clarified. (4) In the process of achieving the goal of China’s tourism carbon neutrality, the number of tourism carbon sink input areas is much larger than that of tourism carbon sink output areas. Accordingly, this paper proposes countermeasures from three aspects: government-led, market system and voluntary mechanisms, in order to promote the achievement of China’s tourism carbon neutrality goal.

Journal

All Earth – Taylor & Francis

Published: Dec 31, 2023

Keywords: Tourism; carbon neutrality; spatial network structure; coupled coordination; spatial and temporal evolution

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