Based on the output and energy consumption data of major industrial products in Henan Province (especially those related to coal), referring to the carbon emission guidelines of the IPCC and combining with multiple linear regression analysis, a carbon emission regression model for Henan Province was constructed. Factor analysis was conducted using SPSS 27.0 software to calculate the scores of high-quality development of prefecture-level cities, and a low-carbon, green and high-quality development model was established to explore the key driving factors affecting the high-quality development of prefecture-level cities. The following results were obtained. 1) Carbon emissions in Henan Province mainly come from production, transportation, construction and daily life. The eastern, northern and central regions of Henan are the main carbon sources, while carbon sinks are mainly concentrated in forest land and cultivated land, which makes the carbon sink storage in the western and southern regions of Henan relatively high. 2) The level of low-carbon, green and high-quality development in Henan Province is on the rise, with significant spatial differences in the calculated scores. Specifically, Zhengzhou City (253), Nanyang City (53) and Luoyang City (49) rank the top three. 3) Zhoukou City has a relatively high score (21) for low-carbon, green and high-quality development, but its total carbon emissions are relatively low (4.28×10⁶ t), and its carbon emissions per unit of energy are relatively high. It belongs to an industrial factor-driven development model. Pingdingshan City has a relatively low score (–25) in low-carbon, green and high-quality development, a high total carbon emission (1.16×10⁷ t), and a high carbon emission per unit of population. It belongs to a development model driven by population factors. 4) To promote high-quality regional development and provide a favorable external development environment, Henan Province should optimize the industrial structure, adjust the energy consumption structure, promote balanced regional development, optimize the industrial layout and improve the ecological compensation mechanism. 

基于河南省主要工业产品产量及能源消耗数据(尤其是煤炭相关工业), 参考IPCC的碳排放准则, 结合多元线性回归分析, 构建河南省碳排放回归模型。运用SPSS 27.0软件进行因子分析, 计算各地级城市高质量发展得分, 并建立低碳绿色高质量发展模型, 探究影响地级城市高质量发展的关键驱动因素, 得到以下结果。1) 河南省碳排放主要来源于生产、交通、建筑和生活等方面, 豫东、豫北和豫中地区是主要碳源地, 碳汇则主要集中在林地和耕地, 使得豫西、豫南地区碳汇储量较高。2) 河南省低碳绿色高质量发展水平呈上升趋势, 空间差异显著, 郑州市(253 分)、南阳市(53 分)和洛阳市(49 分)位列前三。3) 周口市的低碳绿色高质量发展得分较高(21 分), 但碳排放总量较低(4.28×10⁶ t), 单位能源碳排放量较高, 属于工业因素驱动型发展模式; 平顶山市的低碳绿色高质量发展得分较低(–25 分), 碳排放总量较高(1.16×10⁷ t), 单位人口碳排放量较高, 属于人口因素驱动型发展模式。4) 为促进区域高质量发展, 提供良好的外部发展环境, 河南省应优化产业结构, 调整能源消费结构, 促进区域平衡发展, 优化产业布局, 完善生态补偿机制。