Univariate stochastic model for predicting carbon monoxide on an urban roadway
by S.M. Shiva Nagendra, Mukesh Khare
International Journal of Environmental Engineering (IJEE), Vol. 1, No. 3, 2009

Abstract: This paper describes the development of the univariate time-series models for forecasting 1-h average carbon monoxide (CO) concentrations during the critical (winter) period. The CO data covering the period from 1st November to 31st December 1999, has been used for the development of Box–Jenkins models at two Air Quality Control Regions (AQCRs) – traffic intersection (AQCR1) and an arterial road (AQCR2) in the Delhi city. The results indicate the model predictions having degree of agreement, 'd_A' as 0.49 (49% of the predictions are error free) and 0.43 (43%) for AQCR1 and AQCR2, respectively. The 'd_A' values indicate that noise term in the univariate model does not take into account the persistence of inversion conditions.

Online publication date: Tue, 11-Aug-2009

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