COVID-19 vaccination status has become a significant factor influencing carbon emissions in recent years. This paper explores the relationship between vaccination programs and CO2 emissions to provide scientific support for future emergency management. The study utilizes daily carbon emissions data and daily vaccination program data from six sectors within the European Union. It compares the accuracy of various machine learning models by incorporating 11 economic control variables. Additionally, it quantitatively decomposes the contribution of each variable to carbon emissions during the pandemic using SHAP values. The findings indicate that the LightGBM model predicts carbon emissions much more accurately than other models. Furthermore, COVID-19-related variables, such as daily vaccination volumes and cumulative vaccination totals, are identified as significant factors affecting carbon emissions.