How to advance China’s carbon emission peak?— A comparative analysis of energy transition in China and the USA

Abstract

This paper investigates carbon emission peak in China based on a comparative analysis of energy transition in China and the United States (US). The LMDI model is adopted to decompose carbon emissions into several driving factors in 2000-2018 for China and the US. Gray forecasting and NAR neural network are combined to predict peak time and identify optimal transition paths. The factor decomposition indicates that energy intensity is the main inhibitory factor for increased carbon emissions, while economic growth and population size are contributors for increased carbon emissions. There are significant differences in the impact of structure effect on carbon emissions in the two countries. The industry decomposition indicates that industry development is a critical inhibitor for increased carbon emissions after 2014 in China. The growth of transport and agriculture are basically contributing to increase carbon emissions in China and the US. The forecast results illustrate that China could complete carbon emission peak by 2030 under the baseline scenario, with a peak volume of 11354.72Mt CO2. Under the industrial structure adjustment scenario, the carbon peak year may be advanced to 2028. While adjusting industrial structure and energy consumption structure at the same time, China could achieve carbon emission peak at 9918.21Mt CO2 in 2025.