ADMS 3.3 Modelling （Atmospheric Dispersion Model System) Summary of Model Features

ADMS 3.3 Comprehensive models Features “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 ADMS Passive dispersion model Pasquill-Gifford Stability Classes (A – G) Wind speed, direction ADMS Boundary Layer Model Boundary layer height Monin – Obukhov length

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 Met Office 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)

Boundary Layer Height (m) Monin – Obukhov Length (m) 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 D 800 ∞ Neutral - Normal UK Day E 3 400 100 Stable F 20 Stable - Still Night G

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 conditions Centre Line Ground Level Concentrations

A1 Conditions Contour Plot Convective - Hot Still Day Stability Class= A; Wind Speed =1m/s; Boundary Layer Height= 1300m; Monin – Obukhov Length =-2)

D5 Conditions Contour Plot Neutral - Normal UK Day Stability Class= D; Wind Speed =5m/s; Boundary Layer Height= 800m; Monin – Obukhov Length = ∞

F2 Conditions Contour Plot Stable - Still Night Stability Class= F; Wind Speed =2m/s; Boundary Layer Height= 100m; Monin – Obukhov Length = 20

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 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

Tall Stack – With Building

Building Effects – 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

Short Stack - With Building

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

With Hill

3D Hill

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

Statistical + Topography 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 ADMS 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

Odour Example - Results

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 ADMS turbulence calculations 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 construct 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 concentration distribution, H(x,y), as a linear combination of Gaussian and uniform distributions: 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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