The fast growth increases in energy use and greenhouse gas emissions in China's tourism industry. This article assessed the carbon emissions of tourist Chengdu's traffic patterns and how they are expected to change between 2005 and 2021 and explains why tourism carbon decoupling is important for sustainable tourism development. In order to investigate how carbon emissions from tourism may expand without necessarily increasing in tandem with GDP and the variables that influence it, the Tapir model and the LMDI (logarithmic mean Divisia index) method were used. In our study, we looked at six important variables, including (1) the number of visitors, (2) the level of tourism spending per capita, (3) the contribution rate of the tourism sector with according to the country's total national income, (4) the amount of passenger traffic relative to GDP, and (5) the energy consumption relative to the volume of passenger traffic. There have been five stages in the correlation: positively charged decoupling, weak decoupling, negative decoupling, strong coupling, and strong decoupling. All of these describe the relationship between the expansion of China's tourist industry and the country's carbon emissions. Findings highlighted the importance of large numbers of visitors, high levels of per-person tourism spending, and low passenger traffic volume per unit of energy consumption as key positive factors. The rise of carbon emissions may also be slowed by increasing the number of passengers transported per unit of GDP. Carbon emissions from tourists in Chengdu are fluctuating, and this influences the city's economy. The findings have significant theoretical and practical implications for Chengdu's transition to a low-carbon economy and for the formulation of policies to reduce emissions. During the research period, most Chinese provinces exhibited ideal decoupling situations. This research has the potential to be used as a scientific resource for guiding the long-term growth as a result of China's tourist sector.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1007/s11356-023-30899-6 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!