Modeling and simulation of multipollutant dispersion from a network of refinery stacks using a multiple cell approach

E. Fatehifar, A. Elkamel*, M. Taheri, W. A. Anderson, S. A. Abdul-Wahab

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Mathematical air pollution modeling represents an essential tool to control and predict atmospheric pollution. In this paper, a multiple cell model for the three-dimensional simulation of pollutants (SO2, CO, NOX, and TH) dispersion from a network of industrial stacks is presented. The model verification was conducted by checking the simulation results for a single stack against experimental data and also against the predictions of the Gaussian Dispersion Model. Simulation runs were also conducted in actual scale in order to illustrate the program on a network of actual refinery stacks. The results are compared with measured data and also with the results obtained from the Industrial Source Complex (ISC) model, and good agreements were obtained. The effects of meteorological parameters (i.e., wind velocity, air temperature, atmospheric stability, and surface roughness) on pollutants dispersion were also investigated, and a sensitivity analysis study was carried out in order to determine the effect of atmospheric conditions and other input parameters on pollutants dispersion. Sensitivity analysis shows that concentration is sensitive to exit concentration and flow rate in comparison with other input parameters. Finally, practical methods for reducing maximum ground level concentrations are recommended and simulated using the proposed model.

Original languageEnglish
Pages (from-to)795-811
Number of pages17
JournalEnvironmental Engineering Science
Volume24
Issue number6
DOIs
Publication statusPublished - 2007

Keywords

  • Multipollutant dispersion
  • Multistack
  • Network of refinery stacks
  • Simulation

ASJC Scopus subject areas

  • Environmental Chemistry
  • Waste Management and Disposal
  • Pollution

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