International tourism as a cause of global warming is a controversial and topical issue. Here, we use the novel Morlet Wavelet time–frequency approach to gain a deeper insight into the dynamic nexus between tourism, renewable energy utilization, energy utilization and carbon dioxide emissions for China using annual data over the era 1974–2016. The techniques we use include Continuous Wavelet power spectrum, the Wavelet Coherency, and the Partial and the Multiple Wavelet Coherence for time–frequency decomposition that can capture local oscillatory components in time series. Our findings support the hypothesis that tourism can cause increased energy utilization and carbon dioxide emissions in China, which challenges the sustainable tourism development goal. However, on the positive side, the relationship between tourism and renewable energy utilization is shown to facilitate reduced environmental degradation in the medium-long run.