Author(s)

Wenbo Zhao, Zixuan Ge, Juncheng Zhao

Corresponding Author

Wenbo Zhao

Abstract

In the context of global climate change, carbon emissions have become a critical concern. As a major carbon emitter, China’s achievement of its "dual carbon" goals holds significant importance. This study aims to identify key factors influencing China’s carbon emissions and explore future trends. Using the Prophet model to analyze daily carbon emission data from 2020-2024, we found that without major disruptions, emissions show a decreasing trend, potentially achieving peak carbon by 2030, though uncertainties remain. To maximize carbon reduction effects, we evaluated the importance of 14 carbon emission drivers using Pearson correlation coefficients and random forest models. Results revealed that electricity generation, agricultural production, and other variables significantly correlate with carbon emissions. Based on these key factors, we propose specific reduction measures including expanding renewable energy capacity and developing integrated agricultural management models, providing decision-making support for China to achieve its dual carbon goals.

Keywords

Carbon Emissions, Carbon Peak, Prophet Model, Random Forest, Pearson Correlation Coefficient, Emission Reduction Recommendations