In recent years, with the gradual improvement of the public’s demands for ecological and environmental services, changes in environmental quality, especially atmospheric environmental quality, have been highly concerned by the public. Public environmental emotions belong to psychological space information. How to quantify the changes in public environmental emotions caused by changes in environmental quality, comprehensively analyze the atmospheric physical and chemical factors that have a key impact on public environmental emotions, and achieve quantifiable and predictable public environmental emotions are difficult points of current research in the field of public environment. Based on the public participation perception method, this paper proposes a public environmental sentiment prediction model based on the analysis of the relationship between atmospheric environment and public environmental sentiment by using the collected public environmental satisfaction data. Taking the data of a city as an example, using atmospheric environmental factors and public environmental satisfaction, a multiple regression model (OLS) was established, and PM2.5, PM10, temperature (TMP), and humidity (HUM) were used as key factors to conduct Pearson correlation analysis with public environmental satisfaction. The results showed that PM2.5 and PM10 showed a strong negative correlation with public environmental satisfaction (-0.82 and -0.67), while TMP and HUM showed a weak positive correlation with public environmental satisfaction (0.3 and 0.19). Therefore, reducing the concentration of PM2.5 and PM10 in the city has a positive effect on improving public environmental satisfaction.