Upload
lamliem
View
241
Download
10
Embed Size (px)
Citation preview
Comparison of Air Dispersion Modelsincluding ADMS, AERMOD and
CALPUFF
by
Dr David Carruthers
ADMS User Group MeetingVilnius 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
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 ADMS Pre-processor
AERMETPre-processor
CALMETPre-processor
DISPERSION
Boundary layer structure
h, LMO scaling h, LMO scaling h, LMO scaling
Plume rise Advanced integral model Briggs empirical expressions
Briggs empirical expressions
Concentration distribution
Advanced Gaussian plume and puff model
Advanced Gaussian plume model
Non-steady Gaussian puff model
Comparison of ADMS, AERMOD and CALPUFF Model Features
Modelling Feature ADMS AERMOD CALPUFFCOMPLEX EFFECTSBuildings Based on flow model with
near and main building wakes.
Uses PRIME buildings model.
Based on ISC building model.
Complex terrain Based on calculation of flow field and turbulence filed by FLOWSTAR model.
Interpolation between neutral flow approximate solution and stable flow impaction solution.
Effects of complex flow input via meteorological fields.
Deposition (wet and dry)
YES YES YES
Chemistry GRS (Generic Reaction Scheme) 8 reaction scheme for NOxchemistry, parameterised sulphate chemistry.
Ozone limiting model, assumes maximum conversion of NO to NO2.
NOx and SO2 chemistry for particle generation.
Comparison of ADMS, AERMOD and CALPUFF Model Features
Modelling Feature ADMS AERMOD CALPUFFOTHER OPTIONSStreet canyon model YES NO NO
Emissions system EMIT system NO NO
Short term fluctuations for odours, explosions etc
YES NO YES
Visibility Model Condensed plume visibility
NO Visibility Impairment (haze/smog)
Radioactive decay model
YES; includes γ-dose NO NO
Puff Model YES NO Puff release default
Coastline YES NO YES
Input of vertical profiles of met data
YES YES Uses meteorological fields.
VALIDATIONExtensive – 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.
Comparison of ADMS, ARMOD and CALPUFF Model Features
Flat Terrain Validation IMajor study – 24 Field and Wind Tunnel Experiments
Summary Scores for ISC3, ADMS and AERMOD (Different model input parameters)
ISC3 ADMS AERMODBest 5 19 6Middle 2 5 11Worst 17 0 7
ISC3 ADMS AERMODBest 4 8 10Middle 10 15 11Worst 10 1 3
Table 1 from Hanna et al, 6th Workshop on Harmonisation, France Oct 1999Table 2 from Hanna et al, AWMA Meeting, US, June 2000
Table 1
Table 2
Flat terrain II Kincaid power plant Site – flat farmland with some lakes (z0 = 10
cm) Met – 171 hours, neutral to convective Release – 187-m stack, SF6
Results – ns/m3 (normalised by emission rate, quality 3 data)
Data Mean σ Bias NMSE Corr Fac 2
Observations 54.3 40.3 0.0 0.0 1.00 1.00ADMS 4 48.5 31.5 5.9 0.6 0.45 0.68AERMOD ’03 21.8 21.8 32.6 2.1 0.40 0.29
Scatter plots (ns/m3)
Flat terrain III – Kincaid power plant
0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350observed
mod
elle
d
0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350
Observed
AER
MO
D3
ADMS 4 AERMOD
Flat terrain IV– Kincaid power plant
0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350observed
mod
elle
d
0
50
100
150
200
250
300
350
0 50 100 150 200 250 300 350Observed
AER
MO
D
Quantile-quantile plots (ns/m3)ADMS 4 AERMOD
Flat Terrain V - CALPUFF and ISC: Kincaid
Q-Q plot for CALPUFF and ISCST3 (quality 3 data)
Prairie Grass: scatter plot of concentrationsADMS 4.1
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
Prairie Grass: scatter plot of concentrationsAERMOD 02222
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
Prairie Grass: scatter plot of concentrationsISCST2 93109
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
Flat Terrain VI - Prairie Grass
Flat Terrain VII - Prairie Grass
Prairie Grass: q-q plot of concentrationsADMS 4.1
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
Prairie Grass: q-q of concentrationsAERMOD 02222
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
Prairie Grass: q-q of concentrationsISCST2 93109
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
observed
mod
elle
d
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/m3/(g/s))
Two plume approach
Building Effects I
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 PRIME Box model for source in cavity Modified Gaussian for source in cavity Main wake velocity field: wake dimension, velocity and turbulence fields from wall-wake theory
Main wake velocity field: wake dimension from experiment, velocity and turbulence fields from free-wake theory
Main wake has 6 zone dispersion model
Main wake as 2 zone dispersion model
Model applied at all downstream distances
Virtual source model applied far downstream
Building Effects IIIRobins & Castro Experiment
Maximum ground-level concentration as a function of source heightθ=0° and Ws/Ue=3.1
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.5 1.0 1.5 2.0 2.5 3.0Zs/l
K
Experimental ADMS 4.0 ADMS 4.1 ISC-Prime
Building Effects IVRobins & Castro Statistics
Building Effects V Snyder Experiment
Scatter plot of normalised concentrationsADMS 4.1
0
50
100
150
200
250
300
0 50 100 150 200 250 300observed
mod
elle
d
ADMS y=x y=2x y=x/2
Scatter plot of normalised concentrationsISC-Prime
0
50
100
150
200
250
300
0 50 100 150 200 250 300
observed
mod
elle
d
ISC-Prime y=x y=2x y=x/2
Fractional speedup ratio
-0.6
-0.4
-0.2
0.0
0.2
0.4
0.6
0.8
1.0
-1000 -800 -600 -400 -200 0 200 400 600 800 10
Distance from HT (m)
delta
S
AERMOD and ISC use idealised approaches CALPUFF uses 3D time dependent flow field
Complex Terrain I
ADMS Complex Flow Model based on FLOWSTARExample Askervein: Change in speed over hill
-1500 -1000 -500 0 500 1000 1500 20000
250
500
750
-1500 -1000 -500 0 500 1000 1500 20000
250
500
750
0.0
0.5
1.0
1.5
2.0
2.5
5.0
10.0
15.0
20.0
25.0
Ratio of complex terrain to flat terrain maximum concentrations as function of stack height and location
US EPA Wind Tunnel Data
Lawson, Snyder and Thompson (1989)
ADMS
AERMOD
Complex Terrain II: ADMS and AERMOD Comparison in Neutral flow
Complex Terain III ADMS and AERMOD Comparison
369000 375000 381000437000
443000
449000
25
50
75
100
125
150
175
200
225
250
369000 375000 381000437000
443000
449000
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0
MaximumConcentration (ug/m3)
Long Term AverageConcentration (ug/m3)
ADMS (Max=178) ADMS (Max=4.0)
AERMOD (Max=1162) AERMOD (Max=10.3)369000 375000 381000
437000
443000
449000
369000 375000 381000437000
443000
449000
Stack and surrounding terrain, Ribblesdale Valley, North-West England.
Stack height = 100mTerrain = up to 300m
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 IUS CALTRANS Experiment
Layout of roads and receptors
Road Traffic Emissions IIADMS-Roads and CALINE-4
Comparison of trendlines calculated using ADMS Roads and CALINE4 concentrations
0
0.5
1
1.5
2
2.5
0 0.5 1 1.5 2 2.5
Monitored SF6 concentration (ppb)
Cal
cula
ted
SF6 c
once
ntra
tion
(ppb
)
ADMS RoadsCALINE4y=xy=0.5xy=2x
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
M4 calculated and monitored PM10 concentration
0
20
40
60
80
100
120
140
160
20-Jan-97 11-Mar-97 30-Apr-97 19-Jun-97 8-Aug-97
Con
cent
ratio
n (µ
g/m
3)
ADMS RoadsMonitored
ADMS-Roads
Validation Results ADMS-Urban
0
20
40
60
80
100
120
140
0 20 40 60 80 100 120 140
Monitored Data (ppb)
Pred
icte
d D
ata
(ppb
)
NOx Annual AverageNOx Standard DeviationNO2 Annual AverageNO2 PercentileNO2 Standard DeviationO3 annual AverageO3 Standard Deviation
200
400
600
800
200 400 600 800
NOx Percentile
0
20
40
60
80
100
0 20 40 60 80 100
Monitored Data (ug/m3)
Pred
icte
d D
ata
(ug/
m3)
PM10 Annual AveragePM10 90.4 PercentilePM10 98.1 PercentilePM10 Standard Deviation