We aimed to comprehensively investigate the associations of air pollutants with hospital admissions for critical illness in ED. Patients with critical illness including level 1 and level 2 of the Emergency Severity Index admitted in ED of Changsha Central Hospital from January 2016 to December 2020 were enrolled. Meteorological and air pollutants data source were collected from the National Meteorological Science Data Center. A Poisson generalized linear regression combined with a polynomial distributed lag model (PDLM) was utilized to explore the effect of air pollution on hospital admissions for critical illness in ED. Benchmarks as references (25th) were conducted for comparisons with high levels of pollutant concentrations (75th). At first, lagged effects of all different air pollutants were analyzed. Then, based on the most significant factor, analyses in subgroups were performed by gender (male and female), age (< 45, 45-65, and > 65), disorders (cardiovascular, neurological, respiratory), and seasons (spring, summer, autumn, and winter). A total of 47,290 patients with critical illness admitted in ED were included. The effects of air pollutants (PM 2.5 , PM 10 , SO 2 , NO 2 , O 3 and CO) on critical illness ED visits were statistically significant. Strong collinearity between PM 2.5 and PM 10 (r = 0.862) was found. Both single-day lag and cumulative-day lag day models showed that PM 2.5 had the strongest effects (lag 0, RR = 1.025, 95% CI 1.008-1.043, and lag 0-14, RR = 1.067, 95% CI 1.017-1.120, respectively). In both PM 2.5 and PM 10 , the risks of critical illness in male, > 65 ages, respiratory diseases, and winter increased the most significant. Air pollutants, especially PM 2.5 and PM 10 exposure, could increase the risk of critical illness admission.