As an emerging field of eco-efficiency, tourism eco-efficiency is becoming an important way to measure the sustainable development of tourism. This study calculated and decomposed tourism CO₂ emissions in China, explored its evolution and distribution characteristics by using the ratio method of tourism eco-efficiency, and analyzed the influencing factors by adopting a regression model. The results indicate that: (1) tourism CO₂ emissions in China have increased significantly, their largest source is transportation. Its characteristics can be divided into carbon emission intensity factor, income structure factor, consumption level factor, and tourist scale factor through utilizing the Logarithmic Mean Divisia Index (LMDI) method, which also shows that the decisive factor of increased of tourism CO₂ emissions has been the tourist scale factor. (2) Tourism eco-efficiency is marked by spectacular but unstable growth, which can be divided into three stages: inefficient stagnation stage, fluctuating growth stage, and efficient development stage. (3) Tourism eco-efficiency in China has shown that the remarkable high–high cluster and low–low cluster, and the 31 provinces, can be divided into four groups, namely: a high-efficiency high-growth group, a high-efficiency low-growth group, a low-efficiency high-growth group, and a low-efficiency low-growth group. (4) The main influencing factors of tourism eco-efficiency are the scale effect, the structural effect, the technical effect, and the environmental regulation. Since these four factors have different impacts on the tourism eco-efficiency of different groups according to panel data regression, more effective policies should be adopted for the improvement of tourism eco-efficiency in China. Finally, the significances and deficiencies of this study are discussed.

Ethnic areas are special in terms of their geographic type, population size, production mode, etc. Scientific assessment of rural residents’ livelihood resilience and exploration of its influencing factors are significant for tapping the potential of rural residents’ livelihood resilience and promoting sustainable rural development. This research takes the villages in the western Sichuan ethnic area as the study area and, based on the sustainable livelihood framework and the analysis framework of rural residents’ livelihood resilience, constructs an evaluation index system of rural residents’ livelihood resilience and explores the factors affecting its evolution using the OLS parameter estimation method. The results found that: (1) Annual per capita income and livelihood diversification of key livelihood factors of farm households have improved under the rural revitalization strategy. (2) Skill training opportunities, loan opportunities, living conditions, non-agricultural work experience, and traffic accessibility had the most significant impact on livelihood resilience, and were the dominant forces in enhancing the rural residents’ livelihood resilience. (3) There was a divergence of livelihood resilience among different types of rural residents, and those with low altitude, low dependency ratio, strong labor endowment, and high literacy had a higher livelihood resilience; furthermore, the mean value of livelihood resilience of tourism-led rural residents was higher than that of non-tourism-led rural residents under different livelihood strategies.