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Developments of ADMSPresented by
David CarruthersCambridge Environmental ResearchCambridge Environmental Research
Consultants
DMUG, London, 24 November 2005
OutlineADMS3/ADMS4ADMS-Urban/ADMS-RoadsADMS-Airportp
…after ADMS 3?
What applications do you currently use ADMS for?Whi h d l ti t/l t l ?Which model options are most/least popular? Which pollutants are of most/least interest?What scientific capabilities would you like to see in ADMS?What other features would you like to see?Other issues?Other issues?
ProcessUser Group Meeting session, June 2003Feedback from helpdesk, training etcOwn ideasNew scientific information, validationNew scientific information, validationWrote to users in April 2004 seeking iviews
Current Features of
plumes or
ADMS 3
plumes or puffs
NOx chemistry
odours
plume
fluctuations
plume rise
wet deposition
dry deposition
radioactive decay and
d
plume visibility
changes in surface
flow over complex terrain
dispersion
gamma dose
time varying emissions
surface roughness
paround buildings
Meteorology
Issues - Decreasing number of surface met sitesQuality control of meteorological data Use of met model for ‘met data input’Future weather - climate change
Developments - Allowance for input of vertical profilesAllow use of mesoscale model 3D fields and CFD output (building module)
All past years Glasgow data
0° 10°20°
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70°290°
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All future years Glasgow data
0° 10°20°
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Climate Change80°
90°
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280°500
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280°500 Climate Change
Wind roses for Glasgow under the
0
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(knots)
(m/s)
Wind speed
150°160°
170°180°190°200°
210°
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(knots)
(m/s)
Wind speed
150°160°
170°180°190°200°
210°
All past years (summer) Glasgow data
0°
All future years (summer) Glasgow data
0°
Glasgow under the current and future climate scenarios. All year summer and0 10°
20°30°
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90°270°
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2000year, summer, and winter roses are presented. For each scenario the results90
100°
110°
120°
130°
140°
150°160°
170°180°190°200°
210°
220°
230°
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250°
260°
270 90
100°
110°
120°
130°
140°
150°160°
170°180°190°200°
210°
220°
230°
240°
250°
260°
270 scenario, the results are for the four years combined.
0
0
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3.1
10
5.1
16
8.2
(knots)
(m/s)
Wind speed
0
0
3
1.5
6
3.1
10
5.1
16
8.2
(knots)
(m/s)
Wind speed
All past years (winter) Glasgow data
0° 10°20°
30°
40°320°
330°340°
350°
1500
2000
All future years (winter) Glasgow data
0° 10°20°
30°
40°320°
330°340°
350°
1500
2000
50°
60°
70°
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90°
100°
110°250°
260°
270°
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150050°
60°
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90°
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110°250°
260°
270°
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290°
300°
310°
500
1000
1500
0
0
3
1.5
6
3.1
10
5.1
16
8.2
(knots)
(m/s)
Wind speed
110
120°
130°
140°
150°160°
170°180°190°200°
210°
220°
230°
240°
250
0
0
3
1.5
6
3.1
10
5.1
16
8.2
(knots)
(m/s)
Wind speed
110
120°
130°
140°
150°160°
170°180°190°200°
210°
220°
230°
240°
250
Climate ChangeLong term average of NOxfor past (1971, 1976, 1981, 1986) and future , )years (2071, 2076, 2081, 2086) calculated using ADMS 3.2 (point sources) ( )and ADMS-Urban (road source) with Glasgow meteorological data. Note the scale bar does not relate to the large power station plot which covers 16 16k ll th l t16×16km; all other plots are 6×6km and do relate to the scale bar.
Calculated changes in spatial maxima of various NOxconcentration statistics: Glasgow met dataconcentration statistics: Glasgow met data
Wet DepositionCurrent Formation
LCdz∫=∞
F LCdz
Washout coefficient L=APB P precipitation rate
∫=0
wetF
washoutFalling
p p
SO2 - slow rate of uptake/outgassing
gDropMethod (JEP) compared with drop fall time
HCl – limits uptake of SO2
NO – equilibrium with ambient concentration
(JEP)
NO2 – equilibrium with ambient concentrationupdate in drop slow – little deposition
S02 wet depositionS02 et depos t o
8000
10000
8000
10000
4000
6000
8000
6.00 4000
6000
0 05
0.06
-2000
0
2000
Met
res
3.00
4.00
5.00
-2000
0
2000
Met
res
0.03
0.04
0.05
-8000
-6000
-4000
1.00
2.00
-8000
-6000
-4000
0.01
0.02
SO2 wet deposition stable met conditions a) pH limiting washout
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
Metres
-100000 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
Metres
-10000
SO2 wet deposition, stable met conditions a) pH limiting washout coefficient method, b) falling drop method NOTE THESE PLOTS USE DIFFERENT SCALES
Dry DepositionDry Deposition
Current model - Dry deposition velocityCu e t ode y depos t o e oc tyeither specified orcalculated in terms of specified surface roughness and calculated aerodynamic and laminar sub-layer resistance for each hour
Model development -
Express surface resistance in terms of stomatal, leaf surface and soil resistance (Smith et al Atmos Env. 34)
Depends on land use category, solarDepends on land use category, solar radiation, surface roughnessDiurnal and seasonal variations
Dry DepositionLand use category - several vegetation types, canopy height, leaf area index, stomatal response
y epos t o
g , , p
Dry DepositionDry Deposition Resistance Analogy aerodynamic
Laminarsub-layer
soilLeaf
surfacestomatalSurface
resistance
UH
Multiple
Plume of
Interacting wakesBuildings
contaminant from a
dispersion source upwindp
C(y)
Marine boundary layers
Surface roughness, wind and wave t d d tparameters are co-dependent
high waves should be modelled by a high value of surface roughnesssurface roughness
Calculation of the surface sensible heat flux th i diff t f l d d tover the sea is different from over land due to
the difference in latent heat flux
Marine boundary layersSurface roughness and wind profile parameterisation, used by ECMWF (the European Centre for Medium-Range Weather ( p gForecasting)
z v u2
= + ⋅α α *
Surface layer heat flux parameterisation for surface sensible h t fl d l t t h t fl (ECMWF)
zu gm Ch0 = + ⋅α α
*
heat flux and latent heat flux (ECMWF)
−− p zuzcF 0
2 )())(( θθρκ
⎥⎥⎦
⎤
⎢⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛ +−⎟⎟
⎠
⎞⎜⎜⎝
⎛ +
⎥⎥⎦
⎤
⎢⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛ +−⎟⎟
⎠
⎞⎜⎜⎝
⎛ +=
MOMO
H
HH
H
p
Lzz
zzz
Lzz
zzz
F0
0
00
0
0 lnln0
ψψθ
⎥⎥⎦
⎤
⎢⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛ +−⎟⎟
⎠
⎞⎜⎜⎝
⎛ +
⎥⎥⎦
⎤
⎢⎢⎣
⎡⎟⎟⎠
⎞⎜⎜⎝
⎛ +−⎟
⎟⎠
⎞⎜⎜⎝
⎛ +
−−=
sat
Lzz
zzz
Lzz
zzz
zuqzqE
0000
0
lnln
)())((
ψψ
λρκλ
⎥⎦⎢⎣⎟⎠
⎜⎝
⎟⎠
⎜⎝⎥⎦⎢⎣
⎟⎠
⎜⎝⎟
⎠⎜⎝ MOMOqq LzLz 00
Marine boundary layers: u*1 4
1.2
1.4
1
0.6
0.8
Ust
ar (m
/s) USTAR (observed)
USTAR (Charnock = 0.018)
USTAR (Charnock = 0.032)
0.4
USTAR (Charnock = 0.08)
USTAR (standard algorithms)
0.2
Ti i f di t d d b d l f ( / ) t Ch i ti ø Th ti t
0299 300 301 302 303 304 305 306 307 308
day of the year
Time series of predicted and observed values of (m/s) at Christiansø. The time at which the wind direction switched from south-westerly to northerly/easterly (and hence off-shore) is shown by a dotted line
Marine boundary layers: Heat Flux Fθ0Marine boundary layers: Heat Flux Fθ0300
200
250
Predicted
150
a0 (W
/m2)
Predicted
Observed
50
100Fthe
ta
Predicted,standardalgorithms
0
-50299 300 301 302 303 304 305 306 307 308
day of the year
Time series of predicted and observed values of sensible heat flux (W/m2) at Christiansø. The time at which the wind direction switched from south-westerly to northerly/easterly (and hence off-shore) is shown by a dotted line.
ADMS-Urban
ADMS R dADMS-Roads
Noise barriers
M d lli i b iModelling noise barriers
• Noise barriers common in mainland Europe • Effects of noise barriers on pollution of interest –
particularly in residential areas• Looked at results from TNO Traffic model• Modelled noise barriers explicitly in ADMS 3• Derived an empirical algorithm that relates the
noise barrier height to the height of a representative elevated line source
Modelling noise barriers
Modelling noise barriersModelling noise barriers
Background
Look at downstream
windcentreline concentrations
road
barrier “cavity” region
Modelling noise barriers
Concentration µg/m³
ADMS – Urban results (barrier height 6m)
6
4
2
0
Downstream m
0 50 100 150road at x=0
barrier at x=10mx 0 x 10m
Background UK Design Manual for Roads and Bridges (DMRB)
33ac
tor CO
NOx2
men
t fa NOx
PM10
1
Adj
ustm
00 50000 100000 150000 200000
A
0 50000 100000 150000 200000Daily Traffic Flow (AADT)
Initial mixing near vehicles (ADMS-Roads, ADMS U b )ADMS-Urban)Assumes an initial mixing height – 1m.
Ignores different exhaust locations on LGV’s and exhaust buoyancy effects – dependent on wind y y pspeed/vehicle speed.
5(a) Low level exhaust 0km/hr 5(b) High level exhaust 0km/hr
Annual average concentrations for each vehicle type over a range of speeds
30
40CarVanBusLorry horz 4
5
6
10
20
1
2
3
Lorry horzLorry 45 degLorry vert
00 10 20 30 40
Distance down stream (m)
00 10 20 30 40
Distance down stream (m)
Lorry vert
5(c) Low level exhaust 50km/hr
40CarVanBus
5(d) High level exhaust 50km/hr
5
6Lorry horzLorry 45 degLorry vert
10
20
30 Lorry horz
2
3
4
0
10
0 10 20 30 40Distance down stream (m)
0
1
0 10 20 30 40Distance down stream (m)
New parameterisation- dependent on vehicle speed, wind speed- for HGV’s also exhaust location
ADMS Airport(1)ADMS-Airport(1)ADMS-Airport is an extension of ADMS-Urban designed to model pollutant concentrations in the neighbourhood on anmodel pollutant concentrations in the neighbourhood on an airport. It includes all features of ADMS-Urban including the following:gAllowance for up to 6000 sources: road (1500, each with upto 50 vertices), industrial (1500), area sources (3000)•Fully integrated street canyon model based on Danish OSPM model/noise barriers•Local and regional NO chemistry calculation (NO NO and O )•Local and regional NOx chemistry calculation (NO, NO2 and O3)•Based on current understanding of atmospheric boundary layer -characterised by the height of the boundary layer and the Monin-y g y yObukhov length•A meteorological pre-processor – flexible input
ADMS-Airport(2)•Integrated with GIS and Emissions Database. Output via GIS includes high resolution pollutant concentration mapsg p p•‘Local’ ADMS dispersion model nested in trajectory model •ADMS-Urban has been used in many major cities: London,ADMS Urban has been used in many major cities: London, Birmingham, Manchester, Budapest, Beijing, Shanghai, San Diego, Rome, Bologna, Lyon, Dublin etc•ADMS-Urban has been used for many airports across the UK and Ireland (also ADMS 3)
•ADMS-Airport is ADMS-Urban plus the ADMS 3 jet model modified to account of moving jet sources for aircraft take-off roll f f g j f f ffand also additional input options
Neutral met conditions, plume trajectory (zp) (top), vertical spread (σz) (middle) and zp - σz (bottom)
Plume centreline height of the jet exhaust emitted at different points along the runway during take-ffoff
The take-off roll starts at x = 0 with the aircraft moving in the negative x-direction
120
140
160m
)
40
60
80
100
Plum
e ce
ntre
line
heig
ht Z
p (
Difference between plume centreline height and vertical plume spread (Zp - sigma-z) of the jet exhaust emitted at different points along the runway during take-off
The take-off roll starts at x = 0 with the aircraft moving in the negative x-direction
0
20
-1000 -500 0 500 1000 1500
X (m)
Neutral conditions, 5m/s windRelease temperature 232.4 degrees C
The take-off roll starts at x = 0 with the aircraft moving in the negative x-direction
20
0
20
40
Vertical plume spread of the jet exhaust emitted at different points along the runway during take-offThe take-off roll starts at x = 0 with the aircraft moving in the negative x-direction
180-80
-60
-40
-20
Zp -
sigm
a-z
(m)
100
120
140
160
a-z
(m)
-120
-100
-1000 -500 0 500 1000 1500
X (m)
Neutral conditions, 5m/s windRelease temperature 232.4 degrees C
20
40
60
80sigm
Neutral conditions, 5m/s windRelease temperature 232.4 degrees C
0-1000 -500 0 500 1000 1500
X (m)
Scatter plot of monitored and ADMS Airport calculated concentrations of NO (left)Scatter plot of monitored and ADMS-Airport calculated concentrations of NOX (left) and NO2 (right).
Time series of monitored and calculated NOX (top) and NO2 (bottom) in μg/m3 at LHR2
Annual Average NO2 Concentration (μg/m3) Heathrow
Examples pof Polar Plots for HeathrowHeathrow sources
Powerful diagnostic
t ltool
Validation
Arcwise maximum – Harmonisation Meetings etcNear centreline concentrations ASTM methodologygy
ConclusionsADMS 3Meteorology - Input, boundary layer structure, Dry and Wet DepositionBuilding Effects Climate changeBuilding Effects, Climate change
ADMS-Urban, ADMS-RoadsInitial mixing Noise barriersInitial mixing, Noise barriers
ADMS-AirportsJ t M d l f Ai ft E i SJet Model for Aircraft Engine Sources
Input -- PM2.5
Validation, diagnostic techniques
AcknowledgementsDEFRA, Met Office, RWE plus many others
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