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Environmental Science and Pollution Research

, Volume 22, Issue 22, pp 18288–18299 | Cite as

Optimisation of dispersion parameters of Gaussian plume model for CO2 dispersion

  • Xiong Liu
  • Ajit Godbole
  • Cheng Lu
  • Guillaume Michal
  • Philip Venton
Short Research and Discussion Article

Abstract

The carbon capture and storage (CCS) and enhanced oil recovery (EOR) projects entail the possibility of accidental release of carbon dioxide (CO2) into the atmosphere. To quantify the spread of CO2 following such release, the ‘Gaussian’ dispersion model is often used to estimate the resulting CO2 concentration levels in the surroundings. The Gaussian model enables quick estimates of the concentration levels. However, the traditionally recommended values of the ‘dispersion parameters’ in the Gaussian model may not be directly applicable to CO2 dispersion. This paper presents an optimisation technique to obtain the dispersion parameters in order to achieve a quick estimation of CO2 concentration levels in the atmosphere following CO2 blowouts. The optimised dispersion parameters enable the Gaussian model to produce quick estimates of CO2 concentration levels, precluding the necessity to set up and run much more complicated models. Computational fluid dynamics (CFD) models were employed to produce reference CO2 dispersion profiles in various atmospheric stability classes (ASC), different ‘source strengths’ and degrees of ground roughness. The performance of the CFD models was validated against the ‘Kit Fox’ field measurements, involving dispersion over a flat horizontal terrain, both with low and high roughness regions. An optimisation model employing a genetic algorithm (GA) to determine the best dispersion parameters in the Gaussian plume model was set up. Optimum values of the dispersion parameters for different ASCs that can be used in the Gaussian plume model for predicting CO2 dispersion were obtained.

Keywords

CO2 dispersion CFD modelling Gaussian plume model Dispersion parameters Genetic algorithm 

Nomenclature

cp

Specific heat (J kg−1 K−1)

C

Concentration (kg m−3)

Cs

Roughness constant, dimensionless

Cμ

A constant in the k-ε turbulence model

g

Gravitational acceleration (9.8 m s−2)

hs

Release source height (m)

k

Specific turbulent kinetic energy (m2 s−2)

K

von Karman constant ≈ 0.4, dimensionless

Ks

Equivalent sand-grain roughness height (m)

L

Monin-Obukhov length (m)

Q

Release source strength (kg s−1)

Rib

Bulk Richardson number, dimensionless

T

Temperature (K)

u

Wind velocity (m s−1)

ur

Reference wind velocity (m s−1)

u*

Friction velocity (m s−1)

z

Height above ground (m)

zABL

Height of atmospheric boundary layer (m)

zr

Reference height (m)

z0

Surface roughness length (m)

Greek letters

ε

Specific eddy dissipation rate (m2 s−3)

θ

‘Potential’ temperature (K)

σy

Dispersion parameter in Gaussian model (m)

σz

Dispersion parameter in Gaussian model (m)

α

Wind shear exponent, dimensionless

Notes

Acknowledgments

This work is being carried out under the aegis of the Energy Pipelines Cooperative Research Centre (EPCRC), supported through the Australian Government’s Cooperative Research Centre Program, and funded by the Department of Resources, Energy and Tourism (DRET). Cash and in-kind support from the Australian Pipelines Industries Association Research and Standards Committee (APIA RSC) is gratefully acknowledged. The authors wish to express their deep gratitude to Prof. Steven Hanna from the Harvard School of Public Health, and Dr. Joseph Chang from Homeland Security Studies and Analysis Institute, for providing the Kit Fox field experimental data.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Xiong Liu
    • 1
  • Ajit Godbole
    • 1
  • Cheng Lu
    • 1
  • Guillaume Michal
    • 1
  • Philip Venton
    • 2
  1. 1.School of Mechanical, Materials and Mechatronic EngineeringUniversity of WollongongWollongongAustralia
  2. 2.Venton and Associates Pty LtdBundanoonAustralia

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