系统分析长三角三省一市碳排放差异、探究其影响机理及预测碳排放趋势，对促进该区域碳排放协同达峰、实现绿色一体化发展具有重要意义。根据排放系数法测算浙江、江苏、安徽和上海2005~2019年能源消费碳排放量，选择变异系数、基尼系数、泰尔指数分别测度长三角地区碳排放差异。基于STIRPAT拓展模型，采用岭回归探究长三角各省市碳排放的影响机理；运用情景分析法结合各省政策规划及发展规律，参考各变量历史变化率，设定基准发展情景预测长三角各省市2020~2035年碳排放量及碳达峰年份。结果表明：（1）考察期内长三角三省一市碳排放存在显著差异，碳排放差异整体上随着时间推移波动上升。（2）人口数量、城镇化水平、人均GDP、能源强度均显著影响长三角三省一市的碳排放，能源结构仅对江苏的碳排放有显著影响；上海、浙江、安徽的碳排放驱动因素中，产业结构影响最为显著。（3）基准情景下，上海、浙江、安徽和江苏分别在2026、2027、2028和2031年实现碳达峰，峰值依次为 20 768、40 855、63 533和 94 973 万t。

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.