Scientifically estimating and analyzing the spatiotemporal pattern, influencing factors, and scenario predictions of carbon emissions in Yellow River Basin is of great significance for its high-quality development. Firstly, DMSP/OLS and NPP/VIIRS nighttime light data was used to simulate regional carbon emissions from 2000 to 2022 and their spatiotemporal patterns and agglomeration characteristics were analyzed. Secondly, the influencing factors of carbon emissions were analyzed through an extended STIRPAT(stochastic impacts by regression on population, affluence, and technology) model and ridge regression method. Finally, based on the extended STIRPAT model, the development trend of carbon emissions in this region under different scenarios is predicted. The results show that from 2000 to 2022, total carbon emissions in the Yellow River Basin showed an upward trend, with a significant positive global spatial autocorrelation at the prefecture-level city level. Among them, Shanxi, Shaanxi, Ningxia, and Inner Mongolia provinces exhibited “high-high” agglomeration of carbon emissions, while Qinghai, Sichuan, and Gansu provinces exhibited “low-low” agglomeration. Total population, per capita GDP, the proportion of secondary industry output value to GDP, urbanization level, energy structure, and energy intensity all contribute to increased carbon emissions in the Yellow River Basin, while government intervention has an inhibitory effect.Under different scenario predictions, the green development scenario predicts that carbon emissions will peak in 2035, while under the extensive scenario, the peaking time is delayed until 2045.

Yellow River Basin  /  carbon emissions  /  spatiotemporal pattern  /  influencing factors  /  scenario prediction  /  STIRPAT(stochastic impacts by regression on population, affluence, and technology) model