Temporal Variations of Major Air Pollutants and Pollution Standard Index in the Great Tehran Area

Abstract

In this study, the trends of Pollution Standard Index (PSI) and the levels of related air pollutants are analyzed based on the database monitored at two selected roadside air quality monitoring stations: Aghdasieh and Fatemi in Tehran during 2000–2006. The original measured pollutant data and the resultant PSIs are statistically analyzed in different time series, including daily, monthly and seasonal patterns. The daily mean PSIs in seasonal period can be regarded as nonstationary time series. The autoregressive integrated moving average (ARIMA) method implemented by the Box–Jenkins model is used to forecast the PSI time series. The performance evaluations of the adopted models are also carried out and discussed according to Akaike Information Criterion (AIC) and Bayesian information criteria (BIC). The results indicate that both ARIMA (1, 1, 1) and ARIMA (2, 1, 1) models can provide reliable satisfactory predictions for both time series.