ADMS 3.3 Modelling（ Atmospheric Dispersion Model System)

Summary of Model Features

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

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

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

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

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)

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

Example of A – G Conditions

• Stack Release– SO2,150 g/s– 50 m stack– 5 m diameter, – 20 m/s velocity– 15°C

A – G conditionsCentre Line Ground Level Concentrations

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

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

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

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

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

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

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

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

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

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

Topography

• Can effect dispersion– Changes plume trajectory– May increase or decrease concentrations– Include if terrain exceeds 1:10 (maximum 1:3)– Terrain data available

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

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

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

3D Hill

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

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)

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

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

Digital Maps

• Available from Ordnance Survey （ UK)

• 1:50000 or 1:10000

• Can overlay （覆盖） release contours onto maps

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

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

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.

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

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

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

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

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）

Other Features

• Variable surface roughness

• Treatment of land sea internal boundary layer

• Puffs

• NOx Chemistry

• Radioactive decay

• Plume visibility (condensed plume)

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.

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.

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.

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:

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

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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