Objective: To explore the influence of air pollutants (PM2.5, PM10, NO?, SO?) and meteorological factors (temperature, humidity, wind speed, etc.) on the number of visits for respiratory diseases. Methods: This study combined case reports with literature analysis and utilized random forest models and time series analysis data. Results: The study found that pollutants such as PM2.5 and PM10 have a lag effect, and their impacts become apparent after a certain period of exposure. Conclusion: Under extreme weather conditions, the accumulation and diffusion of pollutants are significantly influenced by meteorological conditions. The time series analysis model constructed based on regional air quality, meteorological monitoring, and university outpatient data shows that under unfavorable conditions such as low temperature and low humidity, the increase in pollutant concentration is positively correlated with the number of outpatient visits for respiratory diseases in a non-linear manner.