Optimization of Stack Emission Parameters Using Gaussian Plume Model

Authors

  • Zairi Ali Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Ubaidullah D. Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • M. N. Zahid Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Kahar Osman Faculty of Mechanical Engineering, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v58.1546

Abstract

Numerical simulation is an economical way to control air pollution because of its consistency and ease of use compared to traditional data sampling method. The objective of this research is to develop a practical numerical algorithm to predict the dispersion of pollutant particles around a specific source of emission. The algorithm is tested with a rubber wood manufacturing plant. Gaussian-plume model were used as air dispersion model due to its simplicity and generic application. Results of this study show the concentrations of the pollutant particles on ground level reached approximately 90μg/m3, compared with other software. This value surpasses the limit of 50μg/m3 stipulated by the National Ambient Air Quality Standard (NAAQS) and Recommended Malaysian Guidelines (RMG) set by Environment Department of Malaysia. The manufacturing plant is advised to make a few changes with its emission parameters and adequate values are suggested. In general, the developed algorithm is proven to be able to predict particles distribution around emitted source with acceptable accuracy.

References

O. G. Sutton. 1953. Micrometeorology. London: McGraw-Hill.

F. Pasquill. 1974. Atmospheric Diffusion. 2

nd edition. Chichester: Ellis

Horwood Limited.

A. C. Stern. 1976. Air Pollutants, Their Transformation and Transport.

New York: Academic Press.

M. R. Beychok. 1979. Fundamentals Of Stack Gas Dispersion. Irvine,

California.

K. B. Schnelle and P. R. Dey. 2000. Atmospheric Dispersion Modeling

Compliance Guide. United State of America: McGraw-Hill.

N. K. Arystanbekova, Application of Gaussian Plume Models for Air

Pollution Simulation at Instantaneous Emissions. 2004. Mathematics and

Computer in Simulation.

H. W. M. Witlox. 1994. The HEGADAS Model for Ground-Level HeavyGas Dispersion – I. Steady-State Model. Atmospheric Environment. 28:

–2932.

A. H. Huber. 1991. Wind Tunnel and Gaussian Plume Modeling of

Building Wake Dispersion. Atmospheric Environment. 25(A): 1237–

E. R. Lutman et al. 2004. Comparison Between the Predictions of a

Gaussian Plume Model and a Langrangian Particle Dispersion Model for

Annual Average Calculations of Long-Range Dispersion of

Radionuclides. Journal of Environmental Radioactivity. 339–355.

E. Robertson and P. J. Barry. 1998. The Validity of A Gaussian Plume

Model When Applied to Elevated Releases at A Site On The Canadian

Shield. Atmospheric Environment. 21: 351–362.

E. Lushi, J. M. Stockie. 2009. An Inverse Gaussian Plume Approach for

Estimating Atmospheric Pollutant Emissions from Multiple Point

Sources. Atmospheric Environment. 44: 1097–1107.

C. Leroy, D. Maro, D. Hebert, L. Solier, M. Rozet, S. Le Cavelier, O.

Connan. A Study of the Atmospheric Dispersion of a High Release of

Krypton-85 above a Complex Terrain, Comparison with the Predictions

of Gaussian Models. 2010. Journal of Environmental Radioactivity. Vol

, pp: 937-944.

B. J. Tsuang. Quantification on the source/receptor relationship of

primary pollutants and secondary aerosols by a Gaussian plume model.

Atmospheric Environment. Vol 37, pp:3981-3991.

J. D. Carlson and D. S. Arndt. The Oklahoma Dispersion Model : Using

Gaussian Plume Model as an Operational Management Tool for

Determinaing Near- Surface Dispersion Conditions across Oklahoma.

Journal of Applied Meteorology and Climatology. Vol 47.

N. Sadeghi and M. Sadrnia. Cancer risk assessment for Tehran research

reactor and radioisotope laboratory with CAP88-PC code (Gaussian

plume model). 2011. Nuclear Engineering and Design. Vol 241, pp:1795-

M. R. Beychok. 2005. Fundementals of Stack Gas Dispersion. 4

thEdition.

Irvine, California.

Y. R. Jung, W. G. Park, O. H. Park. Pollution Dispersion Analysis using

the Puff Model with Numerical Flow Field Data. 2003. Mechanics

Research Communication. 30: 277–286.

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Published

2012-07-15

How to Cite

Optimization of Stack Emission Parameters Using Gaussian Plume Model. (2012). Jurnal Teknologi (Sciences & Engineering), 58(2). https://doi.org/10.11113/jt.v58.1546