A seasonal integrated autoregressive moving average (SARIMA) model and a vector autoregressive model (VAR) were applied to modeling the time series of monthly maximum one hour carbon monoxide (CO) concentration in California South Coast Area. The SARIMA model presented how the current month air pollutant concentrations depended upon the previous months air pollutant concentrations. Prediction was made by fitting a model. The VAR models showed the association between the current month CO concentrations and the meteorological covariates including precipitation, temperatures, solar radiation and miles of vehicle travel. Through analysis of the models impulse response function, and forecast error variance decomposition it is demonstrated that: (i)Precipitation does not seem correlated with CO concentration . (ii) Environmental plus traffic elements do exert a long-run effect on CO level (iii)Spurious Regression is an important problem for further data analysis.