AirWare:
Release R5.3 beta
AERMOD/AERMET
DDr. Kurt Fedra
Environmental Software & Services GmbH
A-2352 Gumpoldskirchen AUSTRIA
info@ess.co.at http://www.ess.co.at/AIRWARE
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AERMOD
EPA REGULATORY MODEL, developed from
ISC-ST2/ISC3
AERMOD is a
steady-state Gaussian plume model
Basic assumptions:
• Homogeneous meteorological conditions in
time and space over the aggregation period;
• Constant emissions
• Aggregation period: minimally the time
needed to reach steady state (function of
domain size and wind speed)
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AERMOD
Model provide an analytical solution to the
dispersion equations in 3D;
Horizontal and vertical concentration
distributions are assumed to follow
Gaussian (bell shaped) distribution.
Vertical “complications”:
– Terrain following or impacting;
– Partial reflection at mixing height.
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AERMOD
Basic principle: conservation laws
 y2 
Q
.
C ( x, y , z ) 
. exp(

 2 
2u y z
y 


 z  H eff 2 
 z  H eff 2 
  exp 

exp 






2 z
2 z





where :
C  x, y, z   concent ration at x,y, z
u  windspeed (downwind, m/s)
  S .D.of concent ration in x and y
Q  emission g/s
H eff  effect ivest ack height
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turbulence
ISC used tabulated stability classes (Pasquill)
defined by wind speed, cloud cover,
day/night (heat flux)
AERMOD uses boundary layer physics,
• Roughness length (Monin-Obukhov Length, L)
• surface roughness length, z0
• surface friction velocity, u
• surface heat flux, H
• convective scaling velocity, w .
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turbulence
Roughness length (Monin-Obukhov Length, L)
Measure of “surface roughness”, approximately 1/10 of
obstacle physical vertical dimensions, varies, also
seasonally (vegetation), from
•
•
•
0.0001 m (water surfaces) to
1 m (cities)
1.3 m (forests)
Roughness sub-layer: wind speeds deviates from a vertical
logarithmic profile.
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turbulence
Surface friction velocity, u
Wind speed at reference height corrected by
a vertical logarithmic profile to the
roughness sub-layer and Monin-Obukhov
length.
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turbulence
Monin-Obukhov
length, L,
• A function of
temperature,
• wind speed
• and heat flux.
L
c pTref u 3
kgH
where
g  gravityconstant
c p  specific heat of air
  density of air
k  0.4, von Karman's constant
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H 
turbulence
0.9 Rn
1  1 / B0 
where :
Surface (sensible)
B0  Bowen Rat io
heat flux, H
H  Sensible heat flux
R n  Net Radiat ion
Bowen ratio:
Related to soil
Qh
B

moisture:
Qe
where Qh sensible heat ing(air T )
0.1: wet
Qe lat entheat ing(evaporaton)
i
10: very dry
EF 
Qe
1

Qe  Qh 1  B
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turbulence
1/ 3
 g ' ' '
w   z i  
 Tv

where
g  gravit at ional accelerat on
i
Tv  absolut e temperat re
u
*
Convective scaling
velocity, w .
Now: Deardorff velocity,
scale of wind speed
In the convective mixed
layer:
zi  averagemixinglayer dept h
 ' '  pot ent ialtemperat re
u flux
typically 1 m s-1 …..
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Performance:
Needs to be solved for each source (but
offers the possibility for source
apportioning)
Needs to be solved for each receptor point
(grid cell, but can be solved for any
arbitrary location)
Steady state solution: provides an upper
estimate of concentration
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Data requirements:
• Emission data (stack properties)
• Meteorology:
– Single station data (episode, or 24 hours, one
year (hourly)): wind speed/direction, air
temperature (plume rise)
– Vertical profile (mixing layer) one morning
sounding (value)
– Solar radiation, cloud cover (heat budget)
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AERMET pre-processor:
AERMET operates on data from:
• National Weather Service (NWS)
hourly surface observations,
• NWS twice-daily upper air soundings,
• data collected from an on-site
measurement program such as from
an instrumented tower.
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AERMET data requirements:
Hourly Surface Observations:
• wind speed and direction;
• ambient temperature;
• opaque sky cover; in the absence of opaque sky
cover, total sky cover;
• station pressure is recommended, but not
required,
Upper Air Soundings:
• morning sounding (the 1200 GMT sounding for
applications in the United States).
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AERMOD implementation:
For City/local domains (< 30 km),
• Hourly now-cast runs;
• Daily 24 hour forecast runs;
• Interactive scenario analysis:
– 24 hours daily runs (domains)
– Annual runs (domains);
– EIA for domains (24 hours)
– EIA for single sources (annual, hourly)
– Monitoring station location (annual, hourly)
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AERMOD implementation:
High-resolution (10 m) convolution model
(kernel), for all models that include traffic
emissions (large number of segments).
Includes a mixing-zone approach over the
street surface.
Unit emission kernel scaled for each road
segment (10 m elements).
Transparently integrated with all AERMOD
runs.
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AERMOD configuration:
For each mode of operation (nowcast,
forecast, interactive scenarios, single
source EIA, MS location, traffic)
the model needs:
•A model scenario
•A meteorological scenario
•An emission scenario
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AERMOD scenarios:
Nowcast scenarios are organised by
domain, and shown for the current
(latest) run;
Configuration of a nowcast scenarios:
• Select NEW from the scenario list;
• Edit the scenario (domain,
meteorlogy, emissions)
• Edit the shell script entry (ADMIN only)
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AERMOD implementation
Interactive scenarios:
• 24 hour runs including comparison of
scenarios (domain level impact
assessment);
• High-resolution 1 hour runs for
individual street segments
• Annual runs for monitoring station
location (single source)
• Annual runs for single source impact
assessment.
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AERMOD interactive:
24 hour runs including comparison of
scenarios (domain level impact
assessment);
• Listing of scenarios with name,
simulation date, pollutant simulated,
run status (results, ready to run, running).
• NEW button for creating a new scenario
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AERMOD implementation
Interactive scenarios:
• High-resolution 1 hour runs for
individual street segments
• High resolution kernel/convolutions for
24 hourly runs, transparently combined
with AERMOD for point and area
sources.
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AERMOD implementation
Interactive scenarios:
Annual runs for monitoring station location
(single source):
• Finds the N locations (for possible
monitoring stations) with a user
defined minimum distance
AROUND an emission source with
the highest annual average
concentration over populated
areas.
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AERMOD implementation
Interactive scenarios:
Annual runs for single source impact
assessment:
• Computes annual average
concentration on an hourly basis
around a single source, at user
defined or automatically located
simulated monitoring stations.
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