Scenario Analysis of Carbon Peak Based on PSOBP

Abstract

To investigate the carbon peak scenario and corresponding time in China, this paper firstly employed the grey correlation test to determine the factors influencing carbon emissions; Secondly, PSO-BPNN neural network combined with scenario analysis was used to construct a unique scenario analysis model of China's carbon emissions; Results revealed that: the actual amount of foreign capital utilized, diesel consumption and China's urbanization rate are the three most influential factors on China's carbon emissions. The "double carbon" goals have a long way to go and achieving the carbon peak ahead of schedule requires accelerating the low-carbon energy transition and actively optimizing and upgrading industries but also relies on technological innovation and the promotion of advanced technologies.