Abstract: It is of great significance to systematically analyze the differences in carbon emissions among the three provinces and one municipality in the Yangtze River Delta (YRD) region, explore its impact mechanism and predict the trend of carbon emissions, for promoting the coordinated peaking of carbon emissions in this region and achieving green and integrated development. In this paper, the carbon emissions of energy consumption in Zhejiang, Jiangsu, Anhui and Shanghai from 2005 to 2019 were measured according to the emission coefficient method. The variation coefficient, Gini coefficient and Theil index were selected to measure the carbon emission differences in the YRD region. Based on the STIRPAT expansion model, the ridge regression was used to explore the impact mechanism of carbon emissions in the three provinces and one municipality in the YRD region. Using the scenario analysis method, combined with the policy planning and development law of each province, and referring to the historical rate of change of each variable, a baseline development scenario is set to predict the carbon emissions and carbon peak years of the provinces and cities in the Yangtze River Delta from 2020 to 2035.The results show that: (1) During the investigation period, there were significant differences in carbon emissions among the three provinces and one municipality in the YRD region, and the disparities in carbon emissions fluctuated and increased over time as a whole. (2) Population, urbanization level, GDP per capita, and energy intensity all significantly affect the carbon emissions of the three provinces and one city in the Yangtze River Delta. The energy structure only has a significant impact on the carbon emissions of Jiangsu. In term of the driving factors of carbon emissions in Shanghai, Zhejiang, and Anhui, the industrial structure has the most significant influence on them. (3) Under the baseline scenario, Shanghai, Zhejiang, Anhui and Jiangsu will achieve carbon peaks in 2026, 2027, 2028, and 2031,with peaks of 207.68, 408.55, 635.33 and 949.73 million tons.