Abstract
China's ambitious targets of peaking its Carbon dioxide (CO2) emissions on or before 2030 and achieving carbon neutrality by 2060 have been a topic of discussion in the international community. This study innovatively combines the logarithmic mean Divisia index (LMDI) decomposition method and the long-range energy alternatives planning (LEAP) model to quantitatively evaluate the CO2 emissions from energy consumption in China from 2000 to 2060. Using the Shared Socioeconomic Pathways (SSPs) framework, the study designs five scenarios to explore the impact of different development pathways on energy consumption and related carbon emissions. The LEAP model scenarios are based on the result of LMDI decomposition, which identifies the key influencing factors on CO2 emissions. The empirical findings of this study demonstrate that the energy intensity effect is the primary factor of the 14.7 % reduction in CO2 emissions observed in China from 2000 to 2020. Conversely, the economic development level effect has been the driving factor behind the increase of 50.4 % in CO2 emissions. Additionally, the urbanization effect has contributed 24.7 % to the overall change in CO2 emissions during the same period. Furthermore, the study investigates potential future trajectories of CO2 emissions in China up to 2060, based on various scenarios. The results suggest that, under the SSP1 scenarios. China's CO2 emissions would peak in 2023 and achieve carbon neutrality by 2060. However, under the SSP4 scenarios, emissions are expected to peak in 2028, and China would need to eliminate approximately 2000 Mt of additional CO2 emissions to reach carbon neutrality. In other scenarios, China is projected to be unable to meet the carbon peak and carbon neutrality goals. The conclusions drawn from this study offer valuable insights for potential policy adjustments to ensure that China could fulfill its commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060.
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