adms aermod calpuff
adms aermod calpuff
adms aermod calpuff
Create successful ePaper yourself
Turn your PDF publications into a flip-book with our unique Google optimized e-Paper software.
Comparison of Air Dispersion Models<br />
including ADMS, AERMOD and<br />
CALPUFF<br />
by<br />
Dr David Carruthers<br />
ADMS User Group Meeting<br />
Vilnius 19 January 2010
Well Known Dispersion Models<br />
Short range dispersion model s (upto 50km)<br />
ADMS (ADMS4 Industrial, Roads, Urban, Airports)<br />
AERMOD, ISC, OML, AUSTAL – Industrial releases<br />
CALINE – Road sources<br />
OSPM – Street canyons<br />
AirViro – Urban air quality<br />
Medium range dispersion models<br />
CALPUFF - Regional haze
Comparison of ADMS, AERMOD and CALPUFF Model Features<br />
Modelling Feature ADMS AERMOD CALPUFF<br />
APPLICATIONS<br />
Applications<br />
Up to 50km from<br />
sources; local and urban<br />
scale.<br />
Up to 50km from<br />
sources.<br />
Local and Regional Pollution<br />
Impacts.<br />
SOURCE TYPES<br />
Source types<br />
Point, line (including<br />
road, rail), area, volume,<br />
grid, jet.<br />
Point, line, volume and<br />
area sources.<br />
Point, line, volume, area<br />
METEOROLOGY<br />
Meteorology<br />
DISPERSION<br />
Boundary layer<br />
structure<br />
ADMS<br />
Pre-processor<br />
AERMET<br />
Pre-processor<br />
CALMET<br />
Pre-processor<br />
h, L MO<br />
scaling h, L MO<br />
scaling h, L MO<br />
scaling<br />
Plume rise Advanced integral model Briggs empirical<br />
expressions<br />
Concentration<br />
distribution<br />
Advanced Gaussian<br />
plume and puff model<br />
Advanced Gaussian<br />
plume model<br />
Briggs empirical expressions<br />
Non-steady Gaussian puff<br />
model
Comparison of ADMS, AERMOD and CALPUFF Model Features<br />
Modelling Feature ADMS AERMOD CALPUFF<br />
COMPLEX EFFECTS<br />
Buildings<br />
Complex terrain<br />
Deposition (wet and<br />
dry)<br />
Chemistry<br />
Based on flow model with<br />
near and main building<br />
wakes.<br />
Based on calculation of<br />
flow field and turbulence<br />
filed by FLOWSTAR<br />
model.<br />
Uses PRIME buildings<br />
model.<br />
Interpolation between<br />
neutral flow approximate<br />
solution and stable flow<br />
impaction solution.<br />
Based on ISC building<br />
model.<br />
Effects of complex flow<br />
input via meteorological<br />
fields.<br />
YES YES YES<br />
GRS (Generic Reaction<br />
Scheme) 8 reaction<br />
scheme for NO x<br />
chemistry, parameterised<br />
sulphate chemistry.<br />
Ozone limiting model,<br />
assumes maximum<br />
conversion of NO to NO 2<br />
.<br />
NO x<br />
and SO 2<br />
chemistry<br />
for particle generation.
Comparison of ADMS, ARMOD and CALPUFF Model Features<br />
Modelling Feature ADMS AERMOD CALPUFF<br />
OTHER OPTIONS<br />
Street canyon model YES NO NO<br />
Emissions system EMIT system NO NO<br />
Short term fluctuations<br />
for odours, explosions<br />
etc<br />
Visibility Model<br />
Radioactive decay<br />
model<br />
YES NO YES<br />
Condensed plume<br />
visibility<br />
NO<br />
Visibility Impairment<br />
(haze/smog)<br />
YES; includes γ-dose NO NO<br />
Puff Model YES NO Puff release default<br />
Coastline YES NO YES<br />
Input of vertical<br />
profiles of met data<br />
VALIDATION<br />
YES YES Uses meteorological fields.<br />
Extensive – industrial<br />
point sources, area<br />
sources, road sources,<br />
urban areas, airports.<br />
Extensive – industrial<br />
point sources, area<br />
sources.<br />
Validation of<br />
meteorological f ields,<br />
concentrations and<br />
visibility impacts.
Flat Terrain Validation I<br />
Major study – 24 Field and Wind Tunnel Experiments<br />
Summary Scores for ISC3, ADMS and AERMOD<br />
(Different model input parameters)<br />
Table 1<br />
ISC3 ADMS AERMOD<br />
Best 5 19 6<br />
Middle 2 5 11<br />
Worst 17 0 7<br />
Table 2<br />
ISC3 ADMS AERMOD<br />
Best 4 8 10<br />
Middle 10 15 11<br />
Worst 10 1 3<br />
Table 1 from Hanna et al, 6 th Workshop on Harmonisation, France Oct 1999<br />
Table 2 from Hanna et al, AWMA Meeting, US, June 2000
Flat terrain II Kincaid power plant<br />
• Site – flat farmland with some lakes (z 0 = 10<br />
cm)<br />
• Met – 171 hours, neutral to convective<br />
• Release – 187-m stack, SF 6<br />
• Results – ns/m 3 (normalised by emission rate,<br />
quality 3 data)<br />
Data Mean σ Bias<br />
NMS<br />
E<br />
Corr Fac 2<br />
Observations 54.3 40.3 0.0 0.0 1.00 1.00<br />
ADMS 4 48.5 31.5 5.9 0.6 0.45 0.68<br />
AERMOD ’03 21.8 21.8 32.6 2.1 0.40 0.29
Flat terrain III – Kincaid power plant<br />
• Scatter plots (ns/m 3 )<br />
350<br />
ADMS 4<br />
350<br />
AERMOD<br />
300<br />
300<br />
250<br />
250<br />
modelled<br />
200<br />
150<br />
AERMOD3<br />
200<br />
150<br />
100<br />
100<br />
50<br />
50<br />
0<br />
0 50 100 150 200 250 300 350<br />
observed<br />
0<br />
0 50 100 150 200 250 300 350<br />
Observed
Flat terrain IV– Kincaid power<br />
plant<br />
• Quantile-quantile plots (ns/m 3 )<br />
350<br />
ADMS 4<br />
350<br />
AERMOD<br />
300<br />
300<br />
250<br />
250<br />
modelled<br />
200<br />
150<br />
AERMOD<br />
200<br />
150<br />
100<br />
100<br />
50<br />
50<br />
0<br />
0 50 100 150 200 250 300 350<br />
observed<br />
0<br />
0 50 100 150 200 250 300 350<br />
Observed
Flat Terrain V - CALPUFF and ISC: Kincaid<br />
Q-Q plot for CALPUFF and ISCST3 (quality 3 data)
Flat Terrain VI - Prairie Grass<br />
Prairie Grass: scatter plot of concentrations<br />
ADMS 4.1<br />
Prairie Grass: scatter plot of concentrations<br />
AERMOD 02222<br />
Prairie Grass: scatter plot of concentrations<br />
ISCST2 93109<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed
Flat Terrain VII - Prairie Grass<br />
Prairie Grass: q-q plot of concentrations<br />
ADMS 4.1<br />
Prairie Grass: q-q of concentrations<br />
AERMOD 02222<br />
Prairie Grass: q-q of concentrations<br />
ISCST2 93109<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed<br />
modelled<br />
40<br />
35<br />
30<br />
25<br />
20<br />
15<br />
10<br />
5<br />
0<br />
0 5 10 15 20 25 30 35 40<br />
observed
Flat Terrain VIII Power Plant Comparison: H = 200 m; Exit velocity = 22 m/s<br />
ADMS<br />
ADMS Met/AERMOD Dispersion<br />
Mean<br />
Conc.<br />
100th<br />
percentile
Flat Terrain IX Comparing ADMS and ADMS/AERMOD (converter 1)<br />
Long term runs: Maximum normalised concentration (µg/m 3 /(g/s))
Building<br />
Effects I<br />
• Two plume<br />
approach
Building Effects II: ADMS,<br />
AERMOD and ISC<br />
• PRIME model used in AERMOD (and ISC) is<br />
similar in approach to the ADMS buildings<br />
model.<br />
• Differences between ADMS buildings module<br />
and PRIME<br />
ADMS<br />
Box model for source in cavity<br />
Main wake velocity field: wake<br />
dimension, velocity and turbulence<br />
fields from wall-wake theory<br />
Main wake has 6 zone dispersion<br />
model<br />
Model applied at all downstream<br />
distances<br />
PRIME<br />
Modified Gaussian for source in cavity<br />
Main wake velocity field: wake<br />
dimension from experiment, velocity<br />
and turbulence fields from free-wake<br />
theory<br />
Main wake as 2 zone dispersion model<br />
Virtual source model applied far<br />
downstream
Building Effects III<br />
Robins & Castro Experiment<br />
K<br />
0.40<br />
0.35<br />
0.30<br />
0.25<br />
0.20<br />
0.15<br />
0.10<br />
0.05<br />
Maximum ground-level concentration as a function of source height<br />
θ=0° and Ws/Ue=3.1<br />
Experimental ADMS 4.0 ADMS 4.1 ISC-Prime<br />
0.00<br />
0.5 1.0 1.5 2.0 2.5 3.0<br />
Zs/l
Building Effects IV<br />
Robins & Castro Statistics
Building Effects V<br />
Snyder Experiment<br />
Scatter plot of normalised concentrations<br />
ADMS 4.1<br />
Scatter plot of normalised concentrations<br />
ISC-Prime<br />
ADMS y=x y=2x y=x/2<br />
ISC-Prime y=x y=2x y=x/2<br />
300<br />
300<br />
250<br />
250<br />
200<br />
200<br />
modelled<br />
150<br />
modelled<br />
150<br />
100<br />
100<br />
50<br />
50<br />
0<br />
0 50 100 150 200 250 300<br />
observed<br />
0<br />
0 50 100 150 200 250 300<br />
observed
Complex Terrain I<br />
ADMS Complex Flow Model based on FLOWSTAR<br />
Example Askervein: Change in speed over hill<br />
Fractional speedup ratio<br />
1.0<br />
0.8<br />
0.6<br />
0.4<br />
delta S<br />
0.2<br />
0.0<br />
-1000 -800 -600 -400 -200 0 200 400 600 800 10<br />
-0.2<br />
-0.4<br />
-0.6<br />
Distance from HT (m)<br />
• AERMOD and ISC use idealised approaches<br />
• CALPUFF uses 3D time dependent flow field
Complex Terrain II: ADMS and AERMOD<br />
Comparison in Neutral flow<br />
US EPA Wind Tunnel Data<br />
Lawson, Snyder and<br />
Thompson (1989)<br />
Ratio of complex terrain<br />
to flat terrain maximum<br />
concentrations as<br />
function of stack height<br />
and location<br />
ADMS<br />
AERMOD<br />
750<br />
500<br />
250<br />
0<br />
-1500 -1000 -500 0 500 1000 1500 2000<br />
750<br />
500<br />
250<br />
0<br />
-1500 -1000 -500 0 500 1000 1500 2000<br />
25.0<br />
20.0<br />
15.0<br />
10.0<br />
5.0<br />
2.5<br />
2.0<br />
1.5<br />
1.0<br />
0.5<br />
0.0
Complex Terain III ADMS and AERMOD Comparison<br />
Maximum<br />
Concentration (ug/m3)<br />
Long Term Average<br />
Concentration (ug/m3)<br />
ADMS (Max=178)<br />
ADMS (Max=4.0)<br />
449000<br />
449000<br />
443000<br />
437000<br />
369000 375000 381000<br />
449000<br />
250<br />
225<br />
200<br />
175<br />
150<br />
125<br />
100<br />
443000<br />
437000<br />
369000 375000 381000<br />
449000<br />
5.0<br />
4.5<br />
4.0<br />
3.5<br />
3.0<br />
2.5<br />
2.0<br />
Stack and surrounding<br />
terrain, Ribblesdale Valley,<br />
North-West England.<br />
443000<br />
75<br />
50<br />
25<br />
443000<br />
1.5<br />
1.0<br />
0.5<br />
Stack height = 100m<br />
Terrain = up to 300m<br />
437000<br />
369000 375000 381000<br />
AERMOD (Max=1162)<br />
437000<br />
369000 375000 381000<br />
AERMOD (Max=10.3)
Complex Terrain IV, CALPUFF: Wyoming study<br />
• Meteorology<br />
– 4 upper air stations<br />
– 22 surface stations<br />
– 44 precipitation stations<br />
– MM5 fields<br />
• Terrain<br />
– 4 km resolution<br />
• Receptors<br />
– in Class 1 Wilderness area
Complex Terrain V: CALPUFF, Wyoming case
Road Traffic Emissions I<br />
US CALTRANS Experiment<br />
• Layout of<br />
roads and<br />
receptors
Road Traffic Emissions II<br />
ADMS-Roads and CALINE-4<br />
Comparison of trendlines calculated using ADMS Roads and CALINE4 concentrations<br />
2.5<br />
2<br />
Calculated SF 6 concentration (ppb)<br />
1.5<br />
1<br />
ADMS Roads<br />
CALINE4<br />
y=x<br />
y=0.5x<br />
y=2x<br />
0.5<br />
0<br />
0 0.5 1 1.5 2 2.5<br />
Monitored SF 6 concentration (ppb)<br />
Figure 1 Comparison of trendlines calculated from ADMS-Roads and CALINE4 concentrations
Summary<br />
• Dispersion models in use in Europe include ADMS,<br />
AERMOD, CALPUFF, OML and AUSTAL.<br />
• Key features of the dispersion models ADMS, AERMOD<br />
and CALPUFF been have presented and contrasted.<br />
• Where data are available the models are compared with<br />
each other and with field and wind tunnel data.<br />
• CALPUFF was developed for assessing medium range<br />
impacts of major pollution sources. It requires<br />
meteorological fields as input.
ADMS-Roads<br />
Model Capabilities<br />
ADMS-Roads (Part of ADMS-EIA) is designed to model<br />
dispersion scenarios from single or multiple roads.<br />
• Calculates emissions from traffic flows or accepts<br />
calculated emissions<br />
• Allows many road sources<br />
• Fully integrated street canyon model based on Danish<br />
OSPM model<br />
• Includes impact of traffic induced turbulence on dispersion<br />
• Integrated with Geographical Information Systems (GIS)<br />
and an Emissions Inventory Database
ADMS-Roads<br />
M4 calculated and monitored PM10 concentration<br />
160<br />
140<br />
ADMS Roads<br />
Monitored<br />
120<br />
Concentration (µg/m3)<br />
100<br />
80<br />
60<br />
40<br />
20<br />
0<br />
20-Jan-97 11-Mar-97 30-Apr-97 19-Jun-97 8-Aug-97
Validation Results ADMS-Urban<br />
140<br />
NOx Annual Average<br />
PM10 Annual Average<br />
120<br />
NOx Standard Deviation<br />
NO2 Annual Average<br />
NO2 Percentile<br />
100<br />
PM10 90.4 Percentile<br />
PM10 98.1 Percentile<br />
PM10 Standard Deviation<br />
NO2 Standard Deviation<br />
100<br />
O3 annual Average<br />
O3 Standard Deviation<br />
80<br />
Predicted Data (ppb)<br />
80<br />
60<br />
800<br />
NOx Percentile<br />
Predicted Data (ug/m3)<br />
60<br />
40<br />
40<br />
600<br />
20<br />
400<br />
20<br />
200<br />
200 400 600 800<br />
0<br />
0<br />
0 20 40 60 80 100 120 140<br />
0 20 40 60 80 100<br />
Monitored Data (ppb)<br />
Monitored Data (ug/m3)