QES-Plume v1.0: A Lagrangian dispersion model
Abstract. Low-cost simulations providing accurate predictions of transport of airborne material in urban areas, vegetative canopies, and complex terrain are demanding because of the small-scale heterogeneity of the features influencing the mean flow and turbulence fields. Common models used to predict turbulent transport of passive scalars are based on the Lagrangian stochastic dispersion model. The Quick Environmental Simulation (QES) tool is a low computational-cost framework developed to provide high-resolution wind and concentration fields in a variety of complex atmospheric-boundary-layer environments. Part of the framework, QES-Plume, is a Lagrangian dispersion code that uses a time-implicit integration scheme to solve the generalized Langevin equations which require mean flow and turbulence fields. Here, QES-plume is driven by QES-Winds, a 3D fast-response model that computes mass-consistent wind fields around buildings, vegetation, and hills using empirical parameterizations, and QES-Turb, a local mixing-length turbulence model. In this paper, the particle dispersion model is presented and validated against analytical solutions to examine QES-Plume’s performance under idealized conditions. In particular, QES-Plume is evaluated against a classical Gaussian-plume model for an elevated continuous point-source release in uniform flow and a non-Gaussian-plume model for an elevated continuous point-source release in a power-law boundary-layer flow. In these cases, QES-plume yields a maximum relative error below 6 % with analytical solutions. In addition, the model is tested against wind-tunnel data for a uniform array of cubical buildings. QES-Plume exhibits good agreement with the experiment with 99 % of matched zeros and 59 % of the predicted concentrations falling within a factor of 2 of the experimental concentrations. Furthermore, results also emphasized the importance of using high-quality turbulence models for particle dispersion in complex environments. Finally, QES-Plume demonstrates excellent computational performance.
Fabien Margairaz et al.
Status: open (until 17 Jun 2023)
- RC1: 'Comment on egusphere-2022-1256', Bertrand Carissimo, 31 Jan 2023 reply
- RC2: 'Comment on egusphere-2022-1256', Jérémy Bernard, 30 May 2023 reply
Fabien Margairaz et al.
Fabien Margairaz et al.
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The paper describes the improvement and validation of an operational model set that allow fast Lagrangian computation of pollutant dispersion in urban area. The paper is clear well structured and well written. Only a few clarification are needed.
The model and the validations are openly available as indicated.
My main regret is that the validation with analytical solutions is performed only with Eulerian solutions. For me it is therfore incomplete and this needs to be done in further work
l33 examples of Eulerian models given are large scale. Examples of micro scale obstacle resolving Eulerian models should be given
l55: the unstable modes are in the numerical solution not the equations. Also they are not really "modes »
idem l 108
l 111: the top boundary conditions is mentioned here but not really discussed in the rest of the paper
Table 1: anisotropy is taken into account for different terrain type ( renal, urban, forest...) but there is no discussion of the impact of atmospheric stability. Why? Please give some argument and some dis
L 185 : the non local background mixing coefficient is based on wind tunnel. How can we justify it for low wind speed strongly stratified real cases?
L 223: a well mixed test is mentioned but without details. Was it performed with obstacles ? as it is more difficult for the scheme ? can you comment on this?
Equation 20: this analytical solution chosen for the validation is a purely Eulerian solution. Therefore we do not expect a good agreement with a Lagrangian solution near the source. Did you compare the near source behavior? What is the Lagrangian time scale (and associated distance from the source?
Eg. 21-26 ; because we are in a uniform flow there is no turbulence production by shear. Can you comment on how this the bulent flow is maintained?
Eq. 27 : this is again an Eulerian solution for which we do not expect a perfect agreement. Why did you not use Taylor's solution which is well suited to Lagrangian validation ?
Figure 5: The concentration gradient at the ground is shaving a stange behavior and is very differen in the model and the analytical solution. A non zero concentration gradient is associated with a deposition flux. Can you check an explain this behavior ?
Figure 8: the modd concentration profiles are more noisy than the measurements. This is unusual and can probably be related to the strong shear discussed en the appendix and linked to the flow wake contruction by the diagnostic wind field. Same of the discussion in the appendix should therefore be moved here. As this is en issue , is there a possibility that the flou es smoothed before computing the derivatives for the turbulence?
L 429: is is mentionned a near source and for source behavior as expected in ce La gran qu'on model. Is it ponible to make this more clear by discussing the La grangian time in the model and experiment?
L 427:"complied" : compiled
Figue 9: ts there an explanation for the points outside the factor of 10?
L464: importance of non local mixing : this is for the wind tunnel what about the real atmosphere ?