A parameterization for sub-grid emission variability
description
Transcript of A parameterization for sub-grid emission variability
Stefano Galmarini, DG-Joint Research Center, IES
S. Galmarini1, J.-F. Vinuesa1 and A. Martilli2
1EC-DG-Joint Research Center, Italy2CIEMAT, Spain
A parameterization for sub-grid emission variability
Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES
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Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES
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Stefano Galmarini, DG-Joint Research Center, IES
How to transfer source intensity variability to upper atmospheric layers?
• Turbulent motions are responsible for creating and generating scalars concentration variance
• In RANS scalar variance is accounted for by means of the variance conservation equations
• The source variability at the surface can be though as a boundary condition of scalar variance equation that will take care of describing its transport in x, y and z, creation and dissipation
Stefano Galmarini, DG-Joint Research Center, IES
Formulation
Stefano Galmarini, DG-Joint Research Center, IES
Equation closure
Stefano Galmarini, DG-Joint Research Center, IES
Approach
10 Km
LES =100 x 100 grid cells, 100 m resolution
10 Km
• U=5m.s-1 • Total duration LES=3hours• The dynamic at the end of the first hour is used to fed FVM (u,v,w,theta). • Then emission is released for 2 two hours. Statistics are done over the last hour.
• Sv3=64% of 5x5km2 (LES-1)• Sv4=36% of 5x5km2(LES-2)• Sv5=25% of 5x5km2(LES-3)
• Sv6=16% of 5x5km2(LES-4)
Release of=0.1 ppb.m.s-1
FVM= 2 x 2 grid cells, 5 km resolution
Stefano Galmarini, DG-Joint Research Center, IES
Source size= 64% 5 km2 grid element
Stefano Galmarini, DG-Joint Research Center, IES
Source size= 16% 5 km2 grid element
Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES
16% surface emission64% surface emission A B
C D
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Results:concentration variance
Stefano Galmarini, DG-Joint Research Center, IES
Virtual monitoring stations
Stefano Galmarini, DG-Joint Research Center, IES
64%
Stefano Galmarini, DG-Joint Research Center, IES
16%
Stefano Galmarini, DG-Joint Research Center, IES
Conclusion
• A simple method to account for variability of emission
• Possibility to add error bars to model results
• Further steps: adding the information on the spatial variability
Stefano Galmarini, DG-Joint Research Center, IES
Results:mean concentration
A B
C D
A B
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D
Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES
Stefano Galmarini, DG-Joint Research Center, IES