Chelani, Asha B and Devotta, Sukumar (2006) Nonlinear Analysis and Prediction of Coarse Particulate Matter Concentration in Ambient Air. Journal of Air and Waste Management Association, 56. pp. 78-84. ISSN 1047-3289

[img] PDF - Published Version
Restricted to Registered users only

Download (2661Kb) | Request a copy


This study attempts to characterize and predict coarse particulate matter(PM10) concentration in ambient air using the concepts of nonlinear dynamical theory.PM10 data, India, was used to study the applicability of the chaos theory. First, the autocorrelation function and fourier power spectrum were used to analyze the behavior of the time-series.The dynamics of the timr-series was additionally studied through correlation integral analysis and phase space reconstruction. The nonlibear predictions were then obtained using local polynominal approximation based on the reconstructed phase space. The results were then compared with the autoregressive model. The results of nonlinear analysis indicated the presence of chaotic character in the PM10 time-series. It was also obsered that the nonlinear local approximation outperforms the autoregressive model, because the observed relative error of prediction for the autoregessive model was greater then the local approximation model. The invariant measures of nonlinear dynamics computed for the predicted time-series using the two models also supported the same findings.

Item Type: Article
Subjects: Air Quality
Air Pollution Effects
Air Pollution Control
Depositing User: Users 4 not found.
Date Deposited: 08 Dec 2011 07:40
Last Modified: 08 Dec 2011 07:40

Actions (login required)

View Item View Item