Predicting China’s carbon emission driven by population factors

Combined neural network model LSTM-IPSO-BP was applied to study factors influencing the intensity and change trend in China’s carbon emission driven by future population and structure changes． It is found that continuous decline in China’s population in the future will lead to increased carbon emission intensity, the rate of population decline is positively correlated with carbon emission intensity． Although improved urbanization level will reduce carbon emission intensity, the slowdown of China’s future urbanization process will increase pressure on carbon emission reduction． Under current policies and development trend of various influencing factors, especially population and structural changes, it is difficult for China to achieve a carbon peak before 2030, therefore the Chinese government needs to strengthen the control of carbon emission policies in the following decade．