By collecting daily data on measles cases, air pollutants, and meteorological data from 2005 to 2009 in Chengguan District of Lanzhou City, semi-parametric generalized additive model (GAM) was used to quantitatively study the impact of air pollutants and meteorological factors on daily measles cases. The results showed that air pollutants and meteorological factors had effect on the number of daily measles cases, and there was a certain lag effect. Except for SO2 and relative humidity, other factors showed statistically significant associations with daily measles cases: NO2 lag 6 days, PM10 and maximum temperature lag 5 days, minimum temperature and average temperature and average air pressure lag 4 days, visibility, and wind speed lag 3 days had the greatest impact on the number of daily measles cases. Under the optimum lag conditions, the number of daily measles cases increased by 15.1%, 17.6%, 7.0%, 116.6%, 98.6%, 85.7%, and 14.4% with the increase of 1 IQR in SO2, NO2, PM10, maximum temperature, minimum temperature, average temperature, and wind speed; with the increase of 1 IQR in average pressure, relative humidity, visibility, and daily measles cases decreased by 12.8%, 9.7%, and 13.1%, respectively. And different factors showed different seasonal effects. The effects of SO2 and temperature factors on daily measles cases were greater in spring and winter, but PM10 in summer.