电力CO₂排放因子是精准核算消费端间接排放的重要参数，也是准确量化消费端CO₂排放路径的核心指标。本文首次探究了2020—2035年省级电力CO₂排放因子的时空特征并与官方来源因子进行对比，全面整合了历史直接排放数据以及精准量化电力消费间接排放的重要性，详细预测了不同情景下2020—2035年省级电力消费间接排放及各省排放路径并量化不同时空精度电力CO₂排放因子对各省排放路径的影响。研究表明：（1）2020—2035年，各省电力CO₂排放因子呈现持续下降趋势，而现有公开的电力CO₂排放因子与本研究省级水平相比存在差异；（2）2010—2020年，电力净调入省份的电力消费间接排放及其占比逐渐增加，北京、上海、浙江等省份占比最高；（3）在情景1和情景3（全国、省级维度因子固定不变情景）下，各省的电力消费间接排放和总排放显著高于情景2和情景4（全国、省级维度因子动态变化情景）的估算结果；情景1和情景2（全国维度因子固定不变、动态变化情景）与情景3和情景4（省级维度因子固定不变、动态变化情景）中的估算结果差异较大；对于如北京、上海、广东等电力消费间接排放占比较大的省份，选取不同空间精度的电力CO₂排放因子对其排放总量影响较为明显，进一步导致相关达峰年的偏移。研究结论对支撑各省碳达峰路径规划、降低电力消费间接排放预测的不确定性具有参考价值。

The power grid CO₂ emission factor is a critical parameter for accurately calculating indirect emissions from the electricity consumption side, serving as a core indicator for precisely quantifying the CO₂ emission pathways at the consumption side. This study explores the temporal and spatial characteristics of the province-level power-grid CO₂ emission factors from 2020 to 2035 and compares them with official-source factors. Moreover, it integrates historical direct-emission data to accurately quantify the importance of indirect emissions from the electricity consumption side. Additionally, it predicts the province-level indirect emissions and emission pathways under different scenarios from 2020 to 2035, quantifying the impacts of power grid CO₂ emission factors with distinct temporal and spatial accuracies on provincial emission pathways. The results indicate that: (1) from 2020 to 2035, the power grid CO₂ emission factors of all provinces are expected to exhibit sustained decreasing trends, and there are disparities between the existing publicly available power-grid CO₂ emission factors and provincial levels in the study. (2) From 2010 to 2020, the indirect emissions from electricity consumption and their proportions in net electricity-importing provinces had gradually increased, with Beijing, Shanghai, and Zhejiang province having the largest proportions. (3) Under Scenarios 1 (constant power-grid CO₂ emission factors on the national level) and 3 (constant power-grid CO₂ emission factors on the provincial level), the indirect emissions from electricity consumption and total emissions of all provinces will be significantly higher than the estimated results in Scenarios 2 (dynamic power-grid CO₂ emission factor on the national level) and 4 (dynamic power-grid CO₂ emission factor on the provincial level). The estimation results of Scenarios 1 and 2 are projected to differ significantly from those of Scenarios 3 and 4. For provinces with large proportions of indirect emissions from electricity consumption, such as Beijing, Shanghai, and Guangdong, selecting power grid CO₂ emission factors with different spatial accuracies is expected to have noticeable impacts on their total emissions, further leading to shifts in their peaking years. The research results can provide a reference for supporting the planning of carbon peaking pathways in various provinces and reducing the uncertainty in indirect emission forecasts.