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This study examined the time–frequency relationship between renewable energy, globalization, economic growth, trade openness, urbanization, and CO2emissions in Asia. The wavelet-based causality framework was utilized to quantify the causal associations in time–frequency space among the variables. The method is favorable as a scaling tool and it unveils the time–frequency dependence among variables with more reliability and it accounts for the seasonality, cycles, or trends extracted from the transformation change over time. The empirical data demonstrated that within the sample period, the substantial causal relationships between the employed variables are primarily focused on the short and medium runs at different frequency scales. The wavelet coherence results provided evidence of a strong association among the variables in the long-run estimation, which is supported by the Trace analysis and the Toda–Yamamoto causality. The findings also revealed that renewable energy and CO2are out of phase and have an anti-cyclic impact, with CO2emissions driving the cycle. A positive co-movement between globalization and CO2emissions was observed with no lag relationship, while the association between trade openness and CO2emissions was seen to be insignificant in the long run. These results have significant policy implications for Asian economies’ long-run sustainable policies. Environmental researchers should take into account lead–lag channels of transmission and the time–frequency nexus between series.