Comparative Analysis of Parameters obtained while Simulating an Air-Pollution Episode

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Comparative Analysis of Parameters obtained while
Simulating an Air-Pollution Episode
Ana M. LazarevskaFaculty of Mechanical
Engineering, Skopje University Sv. Kiril i
Metodij, Skopje, R. Macedonialazana_at_mf.ukim.edu.
mk
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Overview
Application areas of Air Quality, Pollutant
Dispersion and Transport Models
Problem Description
Necessary input data for simulating the air
pollution episode (APE)
Results
Conclusion
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Application areas of Air Quality, Pollutant
Dispersion and Transport Models
1. Regulatory purposes - issuing emission permits
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Problem Description
Simulation of an SO2 air pollution episode

• Analyzed Region Grid, Mesh

• Selection of an episode for simulation

• Selection of a simulation tool CALPUFF vs.
  FLUENT

• Numerical simulation of the selected air
  pollution episode over the region of
  interest (FLUENT, CALPUFF)

• Comparative analysis of the parameters engaged

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Simulation of an SO2 air pollution
episodeAnalyzed region and episode - selection
criteria

• Skopje is the capitol of the R. Macedonia,
  (30 of the population, main industrial center)
  - concentration of polluters -
  represent of APEs

• Simultaneous existence of min.necessary input
  data

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Simulation of an SO2 air pollution
episodeSelection of a simulation tool
CALPUFF approach
multi layer, multi species, non-steady-state
puff dispersion model - simulates effects of
varying (xi,t) meteorological conditions on
pollutant transport, transformation and
removal
contains algorithms/modules for near-source
effects (building downwash, transitional
plume rise, sub-grid scale terrain interactions),
longer range effects (pollutant removal,
chemical transformation, over-water transport
etc.)
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C(s) ground level concentration g/m3. Q(s)
pollutant mass in the puff g. sx,y,z(s)
standard deviation of the Gaussian distribution
(along/across wind and vertical
direction) m da,c(s) distance from puff
center to the receptor (along /
across wind direction) m g(s) vertical term
(multiple reflection from top of ML and surface)
He puff center's effective height above ground
m. h ML height m.
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Simulation of an SO2 air pollution
episodeSelection of a simulation tool (cont.)
FLUENT provides comprehensive modeling
capabilities for incompressible and
compressible fluid flow problems, laminar and
turbulent fluid flow problems. Steady-state or
transient analyses models for transport
phenomena (heat transfer and chemical
reactions) combined with ability to model
complex geometries.
in order to allow comparison try-to-imitate
CALMET/CALPUFF approach
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Simulation of an SO2 air pollution
episodeSelection of a simulation tool (cont.)
grid horizontally / vertically same
distancing
fields of meteorological parameters modeled, as
much as the solver allows, similarly to the
approach in CALMET (hourbyhour)
boundary conditions main flow vel. press.
inlet
modeling of pollution transport (here w.o.
chem.reac.) species transport with Discrete
Phase Model (DPM), which performs Lagrangian
trajectory calculations for dispersed phases
(particles, droplets, or bubbles). 1 step
solution of the main flow 2 step emissions
modeled as point injections 3 step coupling
with the continuous phase (possible)
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Mass Conservation Equation
Sm mass added to the continuous phase from the
dispersed second phase and any
user-defined sources.
Transport Equations for the Standard k-e Model
Gk generation of turbulence kinetic energy due to
mean velocity gradientsGb generation of
turbulence kinetic energy due to buoyancy YM
contribution of fluctuating dilatation in
compressible turbulence to overall dissipation
rate,C1e, C2e, C3e constants. sk, se turbulent
Prandtl numbers for k and e, respectively. Sk,
Se user-defined source terms.
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Species Transport Equations
Yi local mass fraction of each species, Ri net
rate of production by chemical reaction Si rate
of creation by addition from the dispersed phase
plus any user-defined sources.
Heat Transfer to the Droplet
Cp droplet heat capacity (J/kg-K) Tp droplet
temperature (K) h convective heat transfer
coefficient (W/m2 K)T?  temperature of
continuous phase (K)dmp/dt  rate of evaporation
(kg/s)hfg  latent heat (J/kg)ep   particle
emissivity (dimensionless)s Stefan-Boltzmann
constant (5.67 10-8 W/m2 K4) qR radiation
temperature,
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Geophysical PreprocessorGAMBIT
Meteorological boundary conditions (main flow)
FLUENT Solution of the main flow
FLUENT Solution of the discrete phase
FLUENT AnalyzeGraphical visualization,
Animation, Statistics
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FLUENT and CALPUFF Mesh of the Region
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Simulation of an SO2 air pollution
episodeNecessary input data for simulating the
APE
1. Geophysical - surface elevation, LUC,
surface roughness
2. Meteorological - surface and upper air
soundings - modeled
surface and upper air data
3. Emission data - flow and geometry properties
modeled emission
data
4. Receptor data - ground concentrations
5. Mixture properties - species (FLUENT)
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Postprocessing
2. ground concentrations of modeled species
3. Development of the APE
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Results
1. Formation and Development Trends of the APE
are maintained
2. Performance Comparison FLUENT vs. CALPUFF

• Advantages a. aside of the geometry/mesh
  preprocessor GAMBIT, FLUENT alone conducts
  the complete calculation of flow and species
  parameters
• b. Particle tracking avlb. within FLUENT
• c. 3D field of species fraction

- Disadvantages selecting/tuning the proper
model in FLUENT might turn out to be a time
consuming and difficult task
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Conclusion

1. The comparative analysis implies a possibility of
   supplementing the both software packages,
   aiming a better quality of the output

1. However, due to the poor quality of input
   parameters, the analysis shows that formation and
   development of an APE can be predicted only
   qualitatively, i.e. only notification of
   existence / prediction of an APE

1. The outcome certainty is a function of the input
   parameters quality

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Thank you for your attention