Exploring the drivers of energy consumption-related CO₂ emissions in China: a multiscale analysis

The exploration and modeling of the drivers of CO₂ emissions can help make effective CO₂ emission reduction policies. In this study, we examine the drivers of energy consumption-related CO₂ emissions in China during 1978–2014 from a multiscale perspective. Firstly, we use the multivariate empirical mode decomposition model to simultaneously decompose the CO₂ emissions and 17 drivers into several groups of intrinsic mode functions and one group of residues at different timescales. Secondly, we employ the stepwise regression analysis to explore and model the key drivers of CO₂ emissions at different timescales without multicollinearity. The empirical results show that China’s CO₂ emissions have obvious timescales of 6.17 years, 9.25 years, 18.5 years, 37.0 years, and long-term trend. At the short-term timescales, fuel structure and economic structure have significant impacts on CO₂ emissions. At the medium-term timescales, urban population and fuel structure are the major contributors to CO₂ emissions. At the long-term timescale, only per capita GDP has a positive effect on CO₂ emissions. Finally, we propose the policy implications at the short, medium, and long timescales.