Exploring the spatiotemporal impact and pathways of temperature and CO2 concentration based on network approach.

Mitigating carbon dioxide (CO2) emissions and curbing temperature rise hold profound significance for global climate protection and economic advancement, particularly in China. From a climatic systems perspective, the interplay between temperature fluctuations and CO2 emissions remains underexplored. Based on the surface-level 1000 hPa atmospheric temperature (T) and CO2 concentration data for China from 2004 to 2020, with a spatial resolution of 3°×2°, this study introduces a multi-layer network framework with time-lag effects to investigate the interaction patterns between temperature and carbon concentration across regions in China. The study reveals the following key features. (1) The interaction between T and CO2 concentrations exhibit a one-day time lag, particularly pronounced during summer and winter. (2) The strength of these interactions weakens diminishes with increasing geographic distance, while significant links are concentrated in regions approximately 1000 km apart. (3) Directional effects of the two are identified, where CO2 concentration forms a positive influence path on T (CO2→T) to the north. (4) Although the influence path of T on CO2 concentration is sparse, its influence is stronger. Specifically, the negative correlation exhibit significant teleconnection, radiating over a region up to 2000 km from northwest to southeast. This study advances the understanding of the temperature-CO2 feedback mechanism, shedding light on the spatial-temporal dynamics of their interaction. These insights provide a scientific foundation for formulating precise carbon reduction policies and climate adaptation strategies tailored to regional characteristics.