This study aims to evaluate the impacts of international tourism development and green technology innovation on economic growth and carbon dioxide emissions in the top 10 GDP countries between 1995 and 2018. Our preliminary findings reject the preposition of data normality, which instigate us to apply a novel method of moments quantile regression. The overall results suggest that international tourism development facilitates economic growth and increases carbon dioxide emissions asymmetrically across the different levels of economic growth and carbon dioxide emissions. Specifically, the economic growth impacts are relatively large for the comparatively more developed nations while the adverse environmental impacts are relatively larger for the comparatively less-polluted nations; thus, the tourism led-economic growth hypothesis is verified. On the other hand, green technology innovation is found to facilitate economic growth and mitigate carbon dioxide emissions, especially in the context of the relatively more developed and polluted economies.

This study analyzes the effects of increased income and renewable energy on environmental quality, which has been ignored in the existing literature. An important contribution of this study is to analyze the role of renewable and nonrenewable energy in relation to the rising level of carbon emissions in the leading emitting countries. This research further examines the heterogeneous impacts of rising income levels and EKC investigation for CO₂ emissions. The Kao cointegration, generalized method of moments (GMM), random effects, fixed effect (FE) regression models, and panel causality techniques are employed for panel data estimations. The empirical outcomes mention that an increase in income moderates the ratio of consumption of renewable energy to CO₂ emissions. Increased income contributes more to the energy mix, which contributes to environmental pollution, through nonrenewable energy. This research reports policy-relevant critical masses beyond which an increase in income negatively affects the link between renewable energy and CO₂ emissions.

Today, China is the second-largest, fastest-growing economy in the world. This study analyzes asymmetric and time-varying impact of world energy prices (including world energy prices index, world coal prices, world crude oil prices and world natural gas prices) on China’s CO₂ emissions. We used a non-linear ARDL (NARDL) model and wavelet analysis using monthly data from 1992 to 2017. The results based on the NARDL estimate show that world energy prices have an asymmetric impact on CO₂ emissions. However, the results of wavelet pairwise correlation and wavelet-transform coherence suggest that the relationship between world energy prices and CO₂ emissions differs over time and across sectors (i.e. short-term, medium-term, long-term and very long-term). Evidence suggests that ignoring fundamental non-linearities can lead to misleading outcomes. Such empirical results are expected to have a high importance for the efficient design and implementation of world energy prices and Chinese environmental policies.