We applied natural smooth (ns) functions of calendar time with 7 degrees of freedom (df) per year to exclude unmeasured long-term and seasonal trends in the time-series dataset (Peng et al., 2009). We incorporated the ns functions of mean temperature (6 df for the period) and relative humidity (3 df for the period) to adjust for the potential nonlinear confounding effects of weather conditions (Chen et al., 2012). We also included the day of the week as an indicator variable in the basic models. After establishing the basic model, we introduced the air pollutant concentrations into the single-pollutant model one at a time to estimate their associations with asthmatic hospitalization.