Characteristics, decoupling effect, and driving factors of regional tourism's carbon emissions in China.

By revealing the temporal and spatial differentiation of China's regional tourism carbon emissions and its decoupling relationship with tourism economic growth and identifying the key factors affecting tourism carbon emissions, this paper is expected to provide a reference for the formulation and implementation of China's regional tourism industry emission reduction policies and measures. Using the tourism's carbon emission data of 30 provinces (cities) in China from 2007 to 2019, we have established a logarithmic mean Divisia index (LMDI) model to identify the main driving factors of carbon emissions related to tourism and a Tapio decoupling model to analyze the decoupling relationship between tourism's carbon emissions and tourism-driven economic growth. Our analysis suggests that China's regional tourism's carbon emissions are growing significantly with marked differences across its regions. Although there are observed fluctuations in the decoupling relationship between regional tourism's carbon emissions and tourism-driven economic growth in China, the data exhibit a primary characteristic of weak decoupling. Nonetheless, the degree of decoupling is rising to various extents across regions. Three of the five driving factors investigated are also found to affect emissions. Both tourism scale and tourism consumption lead to the growth of tourism's carbon emissions, while energy intensity has a significant effect on reducing emissions. These effects differ across regions.