Title: Modelling ozone levels in an arid region - a dynamically evolving soft computing approach

Authors: Syed Masiur Rahman; A.N. Khondaker; Rouf Ahmad Khan

Addresses: Center for Environment and Water, Research Institute, King Fahd University of Petroleum and Minerals, P.O. Box 713, Dhahran 31261, Saudi Arabia ' Center for Environment and Water, Research Institute, King Fahd University of Petroleum and Minerals, P.O. Box 713, Dhahran 31261, Saudi Arabia ' Center for Environment and Water, Research Institute, King Fahd University of Petroleum and Minerals, P.O. Box 713, Dhahran 31261, Saudi Arabia

Abstract: The primary pollutants may contribute to the increase of ozone levels in the arid regions. Complex interactions between the pollutants and the meteorological variables make the study of this phenomenon more exigent. The dynamically evolving neural fuzzy inference system (DENFIS), as an example of soft computing models, allows the online evolution of both the knowledge and the inference mechanism. It is suitable for real-time applications in producing fairly reliable forecasts. The proposed DENFIS model for two sites in the Empty Quarter (Rub Al-Khali Desert) of Saudi Arabia was developed using the meteorological data collected during the winter and the summer seasons, and the transformed meteorological data. The concentrations of nitrogen oxide (NOx) and their transformations were incorporated as additional inputs for model performance analyses. The mean absolute percentage errors of the model vary from 9.52% to 11.84% with discretion and appreciation of the limitations of the overall model predictions and its performance analyses indicate the viability of application of the adopted online DENFIS modelling approach in short-term modelling of zone levels in arid regions.

Keywords: ozone modelling; DENFIS; Empty Quarter; Rub Al-Khali Desert; Saudi Arabia; soft computing; arid regions; neuro-fuzzy inference system; NFIS; neural networks; fuzzy logic; meteorological variables; nitrogen oxide; NOx; primary pollutants; air pollution; air quality; ozone levels.

DOI: 10.1504/IJEP.2013.058456

International Journal of Environment and Pollution, 2013 Vol.52 No.3/4, pp.155 - 171

Received: 01 Apr 2013
Accepted: 23 Aug 2013

Published online: 28 Feb 2014 *

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