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A Nexus of CO2, Tourism Industry, GDP Growth, and Fossil Fuels

The study investigates the nexus of CO2 emissions, tourism, fossil fuels, and GDP growth using China’s data from 1970 to 2019. The research applied the upset U-molded EKC and the ARDL -models to calculate the time series stationarity variables. The results showed that in the initial enlargement phases, a sophisticated GDP adversely impacts CO2 emissions, then a higher GDP positively influences CO2 emissions. The development of tourism, use of fossil fuels (coal and oil), and population growth show an important influence on CO2 emissions but the use of gas and electricity has little effect on CO2 emissions. In contrast, foreign direct investment besides population development had little effect on increasing CO2 emissions. Retreating foreign direct investment, strengthening the use of sustainable electricity, and improving transportation for explorers, especially the green tourism business, are excellent ways to reduce environmental degradation in China.
- University of Jinan China (People's Republic of)
- University of Portsmouth United Kingdom
- University of Jinan China (People's Republic of)
- Jinan University China (People's Republic of)
- Tianjin University of Commerce China (People's Republic of)
electricity consumption, CO2 emissions, ARDL methods, Environmental sciences, natural gas consumption, GDP growth, GE1-350, FDI inflows
electricity consumption, CO2 emissions, ARDL methods, Environmental sciences, natural gas consumption, GDP growth, GE1-350, FDI inflows
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).3 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
