Wavelet-based techniques to analyze the dynamics of petroleum consumption and CO2 emissions: implications for environmental sustainability and policy

Purpose This study investigates the dynamic relationship between petroleum consumption and carbon dioxide (CO2) emissions in India, highlighting their implications for environmental sustainability and policy formulation. Design/methodology/approach The analysis applies the wavelet coherence methodology to monthly data spanning April 1998 to June 2025. This approach allows for the exploration of time–frequency dependencies and the detection of short, medium and long-term linkages between petroleum consumption and CO2 emissions. Additionally, for complementary validation approach, rolling correlation is used. Findings The results reveal a consistently strong positive association, particularly across medium-to long-term cycles, with variations in petroleum consumption frequently preceding changes in CO2 emissions with also evidence that emissions often lead consumption. Short-term fluctuations are less stable, though significant events such as the COVID-19 pandemic demonstrate clear simultaneous impacts on both variables. These findings confirm the substantial contribution of petroleum consumption to India's CO2 emissions profile indicating a persistent positive (in-phase) relationship. Practical implications The evidence offers valuable insights for policymakers seeking to regulate petroleum demand, reduce carbon intensity and align energy strategies with India's environmental and sustainability goals. Targeted interventions in petroleum consumption management could play a pivotal role in achieving long-term decarbonization objectives. Originality/value This study is among the few to apply wavelet coherence analysis to the petroleum consumption–emissions nexus in India, providing novel evidence on the time-varying dynamics of energy–environment relationship using monthly data from the Indian context. The findings contribute to a deeper understanding of how energy demand patterns affect carbon emissions, thereby informing sustainable energy and climate policy.