An autoregressive/moving average (ARMA) approach and a multiple linear regression (MLR) approach were applied to modeling the time series of monthly maximum 1 hour ozone, carbon monoxide, and nitrogen dioxide concentrations in the city of Bakersfield in the San Joaquin Valley Air Basin. The ARMA model presented how the current month air pollutant concentrations depended upon the previous months air pollutant concentrations. The MLR models showed the associations between the current month concentrations and the meteorological covariates including precipitation, temperatures and solar radiation. By comparing these two models, we concluded that the ARMA models are slightly better in fitting the air pollution data than the MLR models.