adms 3.3 modelling ( atmospheric dispersion model system) summary of model features
TRANSCRIPT
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ADMS 3.3 Modelling( Atmospheric Dispersion Model System)
Summary of Model Features
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ADMS 3.3• Comprehensive models
– “New Generation” Model
– Detailed description of atmosphere based on boundary layer properties
• Features– Point, area, line, volume and jet sources
– Multiple sources and pollutants
– Buildings and Topography
– Plume rise
– Single condition or statistical meteorology
– Odours, radioactivity, plume visibility
– Deposition (Wet and Dry)
– Statistics, long and short term, percentiles
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Factors Influencing Dispersion
– Meteorology• Wind Speed and direction• Atmospheric stability (Monin–Obukhov Length and Boundary
Layer Height)– Release point and conditions
• Elevation ( 排放高度)• Velocity• Temperature• Ground roughness
– Buildings• If > 1/3 stack height
– Topography• If steeper than 1:10 slope
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Meteorology
• Older Models – Passive dispersion model
• Pasquill-Gifford Stability Classes (A – G)
• Wind speed, direction
• ADMS– Boundary Layer Model
• Boundary layer height
• Monin – Obukhov length
• Wind speed, direction
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Meteorological Parameters
• Boundary Layer Height– Height at which surface effects influence dispersion
– ADMS calculates boundary layer properties for different heights based on meteorology
• Monin-Obukhov Length– Measure of height at which mechanical turbulence (机械
湍流) is more significant than convection or stratification (层流)
– ADMS calculates M-O length based on meteorology and ground roughness
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Meteorology Options
• Specific Data• Wind speed, wind direction, date, time, latitude (纬
度) , boundary layer height, cloud cover
• Met Office Data• Statistical data (10 years)
– 2200 lines of data (medium run times)
• Hourly sequential data (1 – 5 years)– Can be used to identify specific conditions for known dates
and times– 8760 lines of data per year (long run times)– Use to compare releases against environmental standards
(preferred option (首选) by EA)
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Meteorology Effects• Typical atmospheric conditions within the UK.
• Pasquill - Gifford Stability Classes as modelled in ADMS
• No exact correlation between boundary layer parameters
Stability Class
Wind Speed (m/s)
Boundary Layer Height
(m)
Monin – Obukhov
Length (m)Conditions
A 1 1300 -2 Convective - Hot Still Day
B 2 900 -10 Convective
C 5 850 -100 Convective
D 5 800 ∞ Neutral - Normal UK Day
E 3 400 100 Stable
F 2 100 20 Stable - Still Night
G 1 100 5 Stable
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Example of A – G Conditions
• Stack Release– SO2,150 g/s– 50 m stack– 5 m diameter, – 20 m/s velocity– 15°C
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A – G conditionsCentre Line Ground Level Concentrations
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A1 Conditions Contour PlotConvective - Hot Still Day
Stability Class= A; Wind Speed =1m/s; Boundary Layer Height= 1300m; Monin – Obukhov Length =-2)
0 200 400 600 800 1000 1200 1400 1600 1800 2000
M etres
SO2 Concentration (ug/m3)
-1000
-800
-600
-400
-200
0
200
400
600
800
1000
Met
res
100
200
300
400
500
600
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D5 Conditions Contour PlotNeutral - Normal UK Day
Stability Class= D; Wind Speed =5m/s; Boundary Layer Height= 800m; Monin – Obukhov Length = ∞
0 200 400 600 800 1000 1200 1400 1600 1800 2000
M etres
SO2 Concentration (ug/m3)
-1000
-800
-600
-400
-200
0
200
400
600
800
1000
Met
res
20
40
60
80
100
120
140
160
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F2 Conditions Contour PlotStable - Still Night
Stability Class= F; Wind Speed =2m/s; Boundary Layer Height= 100m; Monin – Obukhov Length = 20
0 200 400 600 800 1000 1200 1400 1600 1800 2000
M etres
S02 Concentration (ug/m3)
-1000
-800
-600
-400
-200
0
200
400
600
800
1000M
etre
s
3
4
5
6
7
8
9
10
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Buildings
• Can have significant effects– Entrain (夹卷) pollutants into leeward ( 下风
向)– Increased concentrations close to building– Decreased concentrations further away– Only relevant if building >1/3 stack height– ADMS allows 10 buildings
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Building Effects – Tall Stack
• Tall Stack– Release of NOx from a 50 m
stack (3 m diameter, 5 m/s velocity, 30°C, 1 g/s NOx)
– Unstable weather conditions
– Stack is at the centre point of the building
– Building is 30 m high, 30 m wide, 67 m long
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Tall Stack – No Building
0 100 200 300 400 500 600 700 800 900 1000
M etres
NOx Concentration (ug/m3)
-400
-300
-200
-100
0
100
200
300
400
Met
res
2
3
4
5
6
7
8
9
10
11
12
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Tall Stack – With Building
0 100 200 300 400 500 600 700 800 900 1000
M etres
NOx Concentration (ug/m3)
-400
-300
-200
-100
0
100
200
300
400
Met
res
2
4
5
6
7
8
9
10
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Building Effects – Short Stack
• Short Stack– Release of NOx from a 35 m
stack (3 m diameter, 5 m/s velocity, 30°C, 1 g/s NOx)
– Unstable weather conditions
– Stack is at the centre point of the building
– Building is 30 m high, 30 m wide, 67 m long
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Short Stack - Without Building
0 100 200 300 400 500 600 700 800 900 1000
M etres
NOx Concentration (ug/m 3)
-400
-300
-200
-100
0
100
200
300
400M
etre
s
23456789101112131415161718192021222324
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Short Stack - With Building
0 100 200 300 400 500 600 700 800 900 1000
M etres
NOx Concentration (ug/m 3)
-400
-300
-200
-100
0
100
200
300
400
Met
res
23456789101112131415161718192021222324
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Topography
• Can effect dispersion– Changes plume trajectory– May increase or decrease concentrations– Include if terrain exceeds 1:10 (maximum 1:3)– Terrain data available
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Topography Example
– Release of NOx from a 65 m stack
– 5 m diameter
– 5.25 m3/s flowrate
– 69°C,
– 1 kg/s NOx
– Neutral weather conditions • 10 m/s wind
• Boundary layer 1000 m
– Simple hill 2.6 km to the East and 1 km South of the release
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Without Hill
-2000 -1000 0 1000 2000 3000 4000
M etres
NOx Concentration (ug/m3)
-2000
-1000
0
1000
2000
3000
4000
Me
tre
s
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
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With Hill
-2000 -1000 0 1000 2000 3000 4000
M etres
NOx Concentration (ug/m3)
-2000
-1000
0
1000
2000
3000
4000
Met
res
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
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3D Hill
200
300
400
500
600
700
800
900
1000
1100
1200
1300
1400
1500
1600
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Statistical Meteorology
• 10 years statistical data
• 1 – 5 years hourly sequential data
• Can calculate– Annual averages– Percentiles ( 百分位数) (worst case conditions)– No of exceedences/year (年超标数)– Areas affected (影响区域)
• Direct comparison with NAAQS (Legislation)
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Statistical Results
442000 442200 442400 442600 442800 443000 443200 443400 443600 443800
M etres
Long Term SO2 Concentration
374200
374400
374600
374800
375000
375200
375400
375600
375800
376000
Met
res
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
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Statistical + Topography
0.6
0.7
0.8
0.9
1
1.1
1.2
1.3
1.4
1.5
1.6
Reproduced from Ordnance Survey® Panorama Digital Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright 1990. All rights reserved. Licence No. 100040193
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Digital Maps
• Available from Ordnance Survey ( UK)
• 1:50000 or 1:10000
• Can overlay (覆盖) release contours onto maps
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Digital Map Example
Reproduced from Ordnance Survey® 1:10K Raster Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright 1990. All rights reserved. Licence No. 100040193
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Digital Map + Topography + Concentrations
Reproduced from Ordnance Survey® Panorama Digital Data and1:10K Raster Data, by permission of Ordnance Survey® on behalf of the Controller of Her Majesty’s Stationary Office. © Copyright 1990. All rights reserved. Licence No. 100040193
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Odours ( 气味)• Model as Odour Units
– ou: Number of times the mixture must be diluted at STP ( Place ) to reach detection limit of 1 ou.
– ouE: The mass of pollutant that when evaporated into 1 m3 of gas at STP is 1 ou
– Information on detection limit is required.
• ADMS– Input and output in terms of ou or ouE.
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Odour Example
• Release from landfill site– Odours in ouE
– Two area sources, one line source• Landfill 1: 100 m x 100 m, 10 ouE/m2/s• Landfill 2: 100 m x 100 m, 5 ouE/m2/s• Line 1: 200 m, 2 ouE/m/s
– Flat terrain (平原地形) , no buildings– Neutral conditions
• 10 m/s wind• Boundary layer 1000 m
– Short term hourly average concentration
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Odour Example - Sources
0 200 400 600 800 1000 1200 1400
Landfill Site
-600
-400
-200
0
200
400
600
LAN D FILL1
LIN E1
LAN D FILL2
O utput grid
Area/line/volum e source
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Odour Example - Results
0 200 400 600 800 1000 1200 1400
M etres
Landfill Odour Release (ouE)
-600
-400
-200
0
200
400
600M
etre
s
15101520253035404550556065707580859095100
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Time Varying Releases (时变源)
• Release rates often vary with production• Time varying releases
– Hourly sequential meteorological data
– Details of release for each hour of meteorological data
• flow, temperature, concentration, velocity
• Results can differ considerably when compared to average releases
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Fluctuations
• Meteorology usually stable over 1 hour• Turbulence causes short duration fluctuations
• Interest in lower times for exposure – Odours
– NAQS (UK)(SO2, 15 minute mean)
• ADMS turbulence calculations– Percentiles– Probability distribution function– Toxic response (毒性反应)
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Other Features
• Variable surface roughness
• Treatment of land sea internal boundary layer
• Puffs
• NOx Chemistry
• Radioactive decay
• Plume visibility (condensed plume)
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AERMOD model
• AERMOD- AMS/EPA Regulatory Model
• AERMOD was introduced by the US EPA as a
Replacement for ( 取代 ) Industrial Source Complex (ISC) model for estimating the air quality impact of sources for source–receptor distances of kilometers.
• AERMOD is designed to use vertical profiles of wind speed and turbulence measured at the site where the model is applied.
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AERMOD model
AERMOD can accept the following turbulence measurements:
• standard deviation of the horizontal wind component, sy, and standard deviation of the vertical wind component, sw. There are future plans to include other turbulence parameters. Such meteorological observations are usually not available at most sites of interest, and insisting on site-specific measurements is not practical.
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AERMOD model• Thus, AERMOD uses a processor ( 处理模块) to c
onstruct inputs from routinely available
National Weather Service (NWS) surface and upper air data from nearby locations.
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Meandering ( 扩散) in AERMOD• AERMOD accounts for meandering by defining the horizontal concentrati
on distribution, H(x,y), as a linear combination of Gaussian and uniform di
stributions:
• • where the plume distribution is
and the uniform distribution is given by
where r is the source–receptor distance. The weighting factor, fp, is taken as the square of the ratio of the mean vector wind speed, U, to the scalar transport wind, Ueff:
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Meandering in AERMOD
• For a source at height hs, the vertical concentration distribution, S(z), is
• where the vertical plume spread is given by the linear expression
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Meandering in AERMOD
where the random components u and v are chosen from a normal distribution with a zero mean and a standard deviation of :
FROM : A. Venkatram et al. / Atmospheric Environment 38 (2004) 4633–4641;V. Isakov et al. / Atmospheric Environment 41 (2007) 1689–1705
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• 大气新导则会议( 2009-3-6 )• 陕西环境保护局• 王厅长讲话• 4 月 1 日执行新导则(报告书,审批)• 徐大海• Screen 3a model• screen3A.exe (dos 版)极端情况• 确定评价等级• Aermod model• 平坦地形, no2, 输入 o3 浓度
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• 地形,源点,极坐标( r, 角)• DOS 版,需探空资料,没探空,用地面资料形成;稳态
的烟流模式;• 高空(无),计算地面浓度较低; • 第三代模式;静态模式,老导则的后代产品;探空资料问
题? 2 倍误差• Calpuf 模式• 完整;考虑地形; 50km; 复杂流畅;下地面不均匀; Cal
met 边界层气象模式; mm5 资料(中尺度模式);下地面类型; KSP 颗粒模式;光化学模式;能见度模式;流场模式; CALPOST 后处理模式
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• 空气质量模式( calpuff,calpost);