Time series analysis of air pollutants and frequency of emergency visits in a city in the Yangtze River Belt from 2020 to 2022

Obeject To understand the effect of air pollutants exposure on emergency visits in a city in the Yangtze River Belt, China. Methods The daily data of the city from 2020 to 2022 were collected, including the concentration of air pollutants, emergency visits and meteorological data. The generalized additive model (GAM) was used to establish a single-pollutant model and multi-pollutant model, and the maximum effective value of lag days was used as the excess risk (ER) to analyze the effect of air pollutants on daily emergency visits. Results The daily mean concentrations of CO, SO ₂ , NO ₂ , O ₃ , PM _2.5 , and PM ₁₀ were 0.81, 9.70, 32.11, 98.78, 34.61 and 35.04 µg/m ³ , respectively, from 2020 to 2022. 39 910 emergency visits were collected during the study period, with the daily mean number of 36 emergency visits. Spearman correlation analysis obtained a significant correlation between pollutants and meteorological factors. The single-pollutant model showed that for every 10 µg/m ³ increase in the concentrations of CO, NO ₂ , SO ₂ , and PM _2.5 , the ER of emergency visits were 0.017% (0.012% to 0.021%), 0.146% (0.057% to 0.236%), − 0.497% (-0.84% to -0.153%), and 0.069% (0.018% to 0.120%), respectively. The results of the multi-pollutant model analysis indicated that the NO ₂ and CO were significantly associated with emergency visits with 0.425%, 0.034% ER, respectively. Conclusion The findings of this study suggest that exposure to air pollutants in the city from 2020 to 2024 affects emergency visits and have lagging effects, among which NO ₂ and CO tend to have a greater influence.