adms aermod calpuff

Comparison of Air Dispersion Models
including ADMS, AERMOD and
CALPUFF
by
Dr David Carruthers
ADMS User Group Meeting
Vilnius 19 January 2010

Well Known Dispersion Models
Short range dispersion model s (upto 50km)
ADMS (ADMS4 Industrial, Roads, Urban, Airports)
AERMOD, ISC, OML, AUSTAL – Industrial releases
CALINE – Road sources
OSPM – Street canyons
AirViro – Urban air quality
Medium range dispersion models
CALPUFF - Regional haze

Comparison of ADMS, AERMOD and CALPUFF Model Features
Modelling Feature ADMS AERMOD CALPUFF
APPLICATIONS
Applications
Up to 50km from
sources; local and urban
scale.
Up to 50km from
sources.
Local and Regional Pollution
Impacts.
SOURCE TYPES
Source types
Point, line (including
road, rail), area, volume,
grid, jet.
Point, line, volume and
area sources.
Point, line, volume, area
METEOROLOGY
Meteorology
DISPERSION
Boundary layer
structure
ADMS
Pre-processor
AERMET
Pre-processor
CALMET
Pre-processor
h, L MO
scaling h, L MO
scaling h, L MO
scaling
Plume rise Advanced integral model Briggs empirical
expressions
Concentration
distribution
Advanced Gaussian
plume and puff model
Advanced Gaussian
plume model
Briggs empirical expressions
Non-steady Gaussian puff
model

Comparison of ADMS, AERMOD and CALPUFF Model Features
Modelling Feature ADMS AERMOD CALPUFF
COMPLEX EFFECTS
Buildings
Complex terrain
Deposition (wet and
dry)
Chemistry
Based on flow model with
near and main building
wakes.
Based on calculation of
flow field and turbulence
filed by FLOWSTAR
model.
Uses PRIME buildings
model.
Interpolation between
neutral flow approximate
solution and stable flow
impaction solution.
Based on ISC building
model.
Effects of complex flow
input via meteorological
fields.
YES YES YES
GRS (Generic Reaction
Scheme) 8 reaction
scheme for NO x
chemistry, parameterised
sulphate chemistry.
Ozone limiting model,
assumes maximum
conversion of NO to NO 2
.
NO x
and SO 2
chemistry
for particle generation.

Comparison of ADMS, ARMOD and CALPUFF Model Features
Modelling Feature ADMS AERMOD CALPUFF
OTHER OPTIONS
Street canyon model YES NO NO
Emissions system EMIT system NO NO
Short term fluctuations
for odours, explosions
etc
Visibility Model
Radioactive decay
model
YES NO YES
Condensed plume
visibility
NO
Visibility Impairment
(haze/smog)
YES; includes γ-dose NO NO
Puff Model YES NO Puff release default
Coastline YES NO YES
Input of vertical
profiles of met data
VALIDATION
YES YES Uses meteorological fields.
Extensive – industrial
point sources, area
sources, road sources,
urban areas, airports.
Extensive – industrial
point sources, area
sources.
Validation of
meteorological f ields,
concentrations and
visibility impacts.

Flat Terrain Validation I
Major study – 24 Field and Wind Tunnel Experiments
Summary Scores for ISC3, ADMS and AERMOD
(Different model input parameters)
Table 1
ISC3 ADMS AERMOD
Best 5 19 6
Middle 2 5 11
Worst 17 0 7
Table 2
ISC3 ADMS AERMOD
Best 4 8 10
Middle 10 15 11
Worst 10 1 3
Table 1 from Hanna et al, 6 th Workshop on Harmonisation, France Oct 1999
Table 2 from Hanna et al, AWMA Meeting, US, June 2000

Flat terrain II Kincaid power plant
• Site – flat farmland with some lakes (z 0 = 10
cm)
• Met – 171 hours, neutral to convective
• Release – 187-m stack, SF 6
• Results – ns/m 3 (normalised by emission rate,
quality 3 data)
Data Mean σ Bias
NMS
E
Corr Fac 2
Observations 54.3 40.3 0.0 0.0 1.00 1.00
ADMS 4 48.5 31.5 5.9 0.6 0.45 0.68
AERMOD ’03 21.8 21.8 32.6 2.1 0.40 0.29

Flat terrain III – Kincaid power plant
• Scatter plots (ns/m 3 )
350
ADMS 4
350
AERMOD
300
300
250
250
modelled
200
150
AERMOD3
200
150
100
100
50
50
0
0 50 100 150 200 250 300 350
observed
0
0 50 100 150 200 250 300 350
Observed

Flat terrain IV– Kincaid power
plant
• Quantile-quantile plots (ns/m 3 )
350
ADMS 4
350
AERMOD
300
300
250
250
modelled
200
150
AERMOD
200
150
100
100
50
50
0
0 50 100 150 200 250 300 350
observed
0
0 50 100 150 200 250 300 350
Observed

Flat Terrain V - CALPUFF and ISC: Kincaid
Q-Q plot for CALPUFF and ISCST3 (quality 3 data)

Flat Terrain VI - Prairie Grass
Prairie Grass: scatter plot of concentrations
ADMS 4.1
Prairie Grass: scatter plot of concentrations
AERMOD 02222
Prairie Grass: scatter plot of concentrations
ISCST2 93109
modelled
40
35
30
25
20
15
10
5
modelled
40
35
30
25
20
15
10
5
modelled
40
35
30
25
20
15
10
5
0
0 5 10 15 20 25 30 35 40
observed
0
0 5 10 15 20 25 30 35 40
observed
0
0 5 10 15 20 25 30 35 40
observed

Flat Terrain VII - Prairie Grass
Prairie Grass: q-q plot of concentrations
ADMS 4.1
Prairie Grass: q-q of concentrations
AERMOD 02222
Prairie Grass: q-q of concentrations
ISCST2 93109
modelled
40
35
30
25
20
15
10
5
0
0 5 10 15 20 25 30 35 40
observed
modelled
40
35
30
25
20
15
10
5
0
0 5 10 15 20 25 30 35 40
observed
modelled
40
35
30
25
20
15
10
5
0
0 5 10 15 20 25 30 35 40
observed

Flat Terrain VIII Power Plant Comparison: H = 200 m; Exit velocity = 22 m/s
ADMS
ADMS Met/AERMOD Dispersion
Mean
Conc.
100th
percentile

Flat Terrain IX Comparing ADMS and ADMS/AERMOD (converter 1)
Long term runs: Maximum normalised concentration (µg/m 3 /(g/s))

Building
Effects I
• Two plume
approach

Building Effects II: ADMS,
AERMOD and ISC
• PRIME model used in AERMOD (and ISC) is
similar in approach to the ADMS buildings
model.
• Differences between ADMS buildings module
and PRIME
ADMS
Box model for source in cavity
Main wake velocity field: wake
dimension, velocity and turbulence
fields from wall-wake theory
Main wake has 6 zone dispersion
model
Model applied at all downstream
distances
PRIME
Modified Gaussian for source in cavity
Main wake velocity field: wake
dimension from experiment, velocity
and turbulence fields from free-wake
theory
Main wake as 2 zone dispersion model
Virtual source model applied far
downstream

Building Effects III
Robins & Castro Experiment
K
0.40
0.35
0.30
0.25
0.20
0.15
0.10
0.05
Maximum ground-level concentration as a function of source height
θ=0° and Ws/Ue=3.1
Experimental ADMS 4.0 ADMS 4.1 ISC-Prime
0.00
0.5 1.0 1.5 2.0 2.5 3.0
Zs/l

Building Effects IV
Robins & Castro Statistics

Building Effects V
Snyder Experiment
Scatter plot of normalised concentrations
ADMS 4.1
Scatter plot of normalised concentrations
ISC-Prime
ADMS y=x y=2x y=x/2
ISC-Prime y=x y=2x y=x/2
300
300
250
250
200
200
modelled
150
modelled
150
100
100
50
50
0
0 50 100 150 200 250 300
observed
0
0 50 100 150 200 250 300
observed

Complex Terrain I
ADMS Complex Flow Model based on FLOWSTAR
Example Askervein: Change in speed over hill
Fractional speedup ratio
1.0
0.8
0.6
0.4
delta S
0.2
0.0
-1000 -800 -600 -400 -200 0 200 400 600 800 10
-0.2
-0.4
-0.6
Distance from HT (m)
• AERMOD and ISC use idealised approaches
• CALPUFF uses 3D time dependent flow field

Complex Terrain II: ADMS and AERMOD
Comparison in Neutral flow
US EPA Wind Tunnel Data
Lawson, Snyder and
Thompson (1989)
Ratio of complex terrain
to flat terrain maximum
concentrations as
function of stack height
and location
ADMS
AERMOD
750
500
250
0
-1500 -1000 -500 0 500 1000 1500 2000
750
500
250
0
-1500 -1000 -500 0 500 1000 1500 2000
25.0
20.0
15.0
10.0
5.0
2.5
2.0
1.5
1.0
0.5
0.0

Complex Terain III ADMS and AERMOD Comparison
Maximum
Concentration (ug/m3)
Long Term Average
Concentration (ug/m3)
ADMS (Max=178)
ADMS (Max=4.0)
449000
449000
443000
437000
369000 375000 381000
449000
250
225
200
175
150
125
100
443000
437000
369000 375000 381000
449000
5.0
4.5
4.0
3.5
3.0
2.5
2.0
Stack and surrounding
terrain, Ribblesdale Valley,
North-West England.
443000
75
50
25
443000
1.5
1.0
0.5
Stack height = 100m
Terrain = up to 300m
437000
369000 375000 381000
AERMOD (Max=1162)
437000
369000 375000 381000
AERMOD (Max=10.3)

Complex Terrain IV, CALPUFF: Wyoming study
• Meteorology
– 4 upper air stations
– 22 surface stations
– 44 precipitation stations
– MM5 fields
• Terrain
– 4 km resolution
• Receptors
– in Class 1 Wilderness area

Complex Terrain V: CALPUFF, Wyoming case

Road Traffic Emissions I
US CALTRANS Experiment
• Layout of
roads and
receptors

Road Traffic Emissions II
ADMS-Roads and CALINE-4
Comparison of trendlines calculated using ADMS Roads and CALINE4 concentrations
2.5
2
Calculated SF 6 concentration (ppb)
1.5
1
ADMS Roads
CALINE4
y=x
y=0.5x
y=2x
0.5
0
0 0.5 1 1.5 2 2.5
Monitored SF 6 concentration (ppb)
Figure 1 Comparison of trendlines calculated from ADMS-Roads and CALINE4 concentrations

Summary
• Dispersion models in use in Europe include ADMS,
AERMOD, CALPUFF, OML and AUSTAL.
• Key features of the dispersion models ADMS, AERMOD
and CALPUFF been have presented and contrasted.
• Where data are available the models are compared with
each other and with field and wind tunnel data.
• CALPUFF was developed for assessing medium range
impacts of major pollution sources. It requires
meteorological fields as input.

ADMS-Roads
Model Capabilities
ADMS-Roads (Part of ADMS-EIA) is designed to model
dispersion scenarios from single or multiple roads.
• Calculates emissions from traffic flows or accepts
calculated emissions
• Allows many road sources
• Fully integrated street canyon model based on Danish
OSPM model
• Includes impact of traffic induced turbulence on dispersion
• Integrated with Geographical Information Systems (GIS)
and an Emissions Inventory Database

ADMS-Roads
M4 calculated and monitored PM10 concentration
160
140
ADMS Roads
Monitored
120
Concentration (µg/m3)
100
80
60
40
20
0
20-Jan-97 11-Mar-97 30-Apr-97 19-Jun-97 8-Aug-97

Validation Results ADMS-Urban
140
NOx Annual Average
PM10 Annual Average
120
NOx Standard Deviation
NO2 Annual Average
NO2 Percentile
100
PM10 90.4 Percentile
PM10 98.1 Percentile
PM10 Standard Deviation
NO2 Standard Deviation
100
O3 annual Average
O3 Standard Deviation
80
Predicted Data (ppb)
80
60
800
NOx Percentile
Predicted Data (ug/m3)
60
40
40
600
20
400
20
200
200 400 600 800
0
0
0 20 40 60 80 100 120 140
0 20 40 60 80 100
Monitored Data (ppb)
Monitored Data (ug/m3)