1 AirWare : R elease R5.3 beta AERMOD/AERMET DDr. Kurt Fedra Environmental Software & Services GmbH A-2352 Gumpoldskirchen AUSTRIA

2 AERMODAERMOD EPA REGULATORY MODEL, developed from ISC-ST2/ISC3 AERMOD is a steady-state Gaussian plume model Basic assumptions: Homogeneous meteorological conditions in time and space over the aggregation period; Constant emissions Aggregation period: minimally the time needed to reach steady state (function of domain size and wind speed) EPA REGULATORY MODEL, developed from ISC-ST2/ISC3 AERMOD is a steady-state Gaussian plume model Basic assumptions: Homogeneous meteorological conditions in time and space over the aggregation period; Constant emissions Aggregation period: minimally the time needed to reach steady state (function of domain size and wind speed)

3 AERMODAERMOD Model provide an analytical solution to the dispersion equations in 3D; Horizontal and vertical concentration distributions are assumed to follow Gaussian (bell shaped) distribution. Vertical “complications”: –Terrain following or impacting; –Partial reflection at mixing height. Model provide an analytical solution to the dispersion equations in 3D; Horizontal and vertical concentration distributions are assumed to follow Gaussian (bell shaped) distribution. Vertical “complications”: –Terrain following or impacting; –Partial reflection at mixing height.

4 AERMODAERMOD Basic principle: conservation laws

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7 turbulenceturbulence ISC used tabulated stability classes (Pasquill) defined by wind speed, cloud cover, day/night (heat flux) AERMOD uses boundary layer physics, Roughness length (Monin-Obukhov Length, L) surface roughness length, z 0 surface friction velocity, u surface heat flux, H convective scaling velocity, w. ISC used tabulated stability classes (Pasquill) defined by wind speed, cloud cover, day/night (heat flux) AERMOD uses boundary layer physics, Roughness length (Monin-Obukhov Length, L) surface roughness length, z 0 surface friction velocity, u surface heat flux, H convective scaling velocity, w.

8 turbulenceturbulence Roughness length (Monin-Obukhov Length, L) Measure of “surface roughness”, approximately 1/10 of obstacle physical vertical dimensions, varies, also seasonally (vegetation), from m (water surfaces) to 1 m (cities) 1.3 m (forests) Roughness sub-layer: wind speeds deviates from a vertical logarithmic profile. Roughness length (Monin-Obukhov Length, L) Measure of “surface roughness”, approximately 1/10 of obstacle physical vertical dimensions, varies, also seasonally (vegetation), from m (water surfaces) to 1 m (cities) 1.3 m (forests) Roughness sub-layer: wind speeds deviates from a vertical logarithmic profile.

9 turbulenceturbulence Surface friction velocity, u Wind speed at reference height corrected by a vertical logarithmic profile to the roughness sub-layer and Monin-Obukhov length. Surface friction velocity, u Wind speed at reference height corrected by a vertical logarithmic profile to the roughness sub-layer and Monin-Obukhov length.

10 turbulenceturbulence Monin-Obukhov length, L, A function of temperature, wind speed and heat flux. Monin-Obukhov length, L, A function of temperature, wind speed and heat flux.

11 turbulenceturbulence Surface (sensible) heat flux, H Bowen ratio: Related to soil moisture: 0.1: wet 10: very dry Surface (sensible) heat flux, H Bowen ratio: Related to soil moisture: 0.1: wet 10: very dry

12 turbulenceturbulence Convective scaling velocity, w. Now: Deardorff velocity, scale of wind speed In the convective mixed layer: typically 1 m s -1 ….. Convective scaling velocity, w. Now: Deardorff velocity, scale of wind speed In the convective mixed layer: typically 1 m s -1 …..

13 Performance:Performance: Needs to be solved for each source (but offers the possibility for source apportioning) Needs to be solved for each receptor point (grid cell, but can be solved for any arbitrary location) Steady state solution: provides an upper estimate of concentration Needs to be solved for each source (but offers the possibility for source apportioning) Needs to be solved for each receptor point (grid cell, but can be solved for any arbitrary location) Steady state solution: provides an upper estimate of concentration

14 Data requirements: Emission data (stack properties) Meteorology: –Single station data (episode, or 24 hours, one year (hourly)): wind speed/direction, air temperature (plume rise) –Vertical profile (mixing layer) one morning sounding (value) –Solar radiation, cloud cover (heat budget) Emission data (stack properties) Meteorology: –Single station data (episode, or 24 hours, one year (hourly)): wind speed/direction, air temperature (plume rise) –Vertical profile (mixing layer) one morning sounding (value) –Solar radiation, cloud cover (heat budget)

15 AERMET pre-processor: AERMET operates on data from: National Weather Service (NWS) hourly surface observations, NWS twice-daily upper air soundings, data collected from an on-site measurement program such as from an instrumented tower. AERMET operates on data from: National Weather Service (NWS) hourly surface observations, NWS twice-daily upper air soundings, data collected from an on-site measurement program such as from an instrumented tower.

16 AERMET data requirements: Hourly Surface Observations: wind speed and direction; ambient temperature; opaque sky cover; in the absence of opaque sky cover, total sky cover; station pressure is recommended, but not required, Upper Air Soundings: morning sounding (the 1200 GMT sounding for applications in the United States). Hourly Surface Observations: wind speed and direction; ambient temperature; opaque sky cover; in the absence of opaque sky cover, total sky cover; station pressure is recommended, but not required, Upper Air Soundings: morning sounding (the 1200 GMT sounding for applications in the United States).

17 AERMOD implementation: For City/local domains (< 30 km), Hourly now-cast runs; Daily 24 hour forecast runs; Interactive scenario analysis: –24 hours daily runs (domains) –Annual runs (domains); –EIA for domains (24 hours) –EIA for single sources (annual, hourly) –Monitoring station location (annual, hourly) For City/local domains (< 30 km), Hourly now-cast runs; Daily 24 hour forecast runs; Interactive scenario analysis: –24 hours daily runs (domains) –Annual runs (domains); –EIA for domains (24 hours) –EIA for single sources (annual, hourly) –Monitoring station location (annual, hourly)

18 AERMOD implementation: High-resolution (10 m) convolution model (kernel), for all models that include traffic emissions (large number of segments). Includes a mixing-zone approach over the street surface. Unit emission kernel scaled for each road segment (10 m elements). Transparently integrated with all AERMOD runs. High-resolution (10 m) convolution model (kernel), for all models that include traffic emissions (large number of segments). Includes a mixing-zone approach over the street surface. Unit emission kernel scaled for each road segment (10 m elements). Transparently integrated with all AERMOD runs.

19 AERMOD configuration: For each mode of operation (nowcast, forecast, interactive scenarios, single source EIA, MS location, traffic) the model needs: A model scenario A meteorological scenario An emission scenario For each mode of operation (nowcast, forecast, interactive scenarios, single source EIA, MS location, traffic) the model needs: A model scenario A meteorological scenario An emission scenario

20 AERMOD scenarios: Nowcast scenarios are organised by domain, and shown for the current (latest) run; Configuration of a nowcast scenarios: Select NEW from the scenario list; Edit the scenario (domain, meteorlogy, emissions) Edit the shell script entry (ADMIN only) Nowcast scenarios are organised by domain, and shown for the current (latest) run; Configuration of a nowcast scenarios: Select NEW from the scenario list; Edit the scenario (domain, meteorlogy, emissions) Edit the shell script entry (ADMIN only)

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27 AERMOD implementation Interactive scenarios: 24 hour runs including comparison of scenarios (domain level impact assessment); High-resolution 1 hour runs for individual street segments Annual runs for monitoring station location (single source) Annual runs for single source impact assessment. Interactive scenarios: 24 hour runs including comparison of scenarios (domain level impact assessment); High-resolution 1 hour runs for individual street segments Annual runs for monitoring station location (single source) Annual runs for single source impact assessment.

28 AERMOD interactive: 24 hour runs including comparison of scenarios (domain level impact assessment); ready to runListing of scenarios with name, simulation date, pollutant simulated, run status (results, ready to run, running). NEW button for creating a new scenario 24 hour runs including comparison of scenarios (domain level impact assessment); ready to runListing of scenarios with name, simulation date, pollutant simulated, run status (results, ready to run, running). NEW button for creating a new scenario

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32 AERMOD implementation Interactive scenarios: High-resolution 1 hour runs for individual street segments High resolution kernel/convolutions for 24 hourly runs, transparently combined with AERMOD for point and area sources. Interactive scenarios: High-resolution 1 hour runs for individual street segments High resolution kernel/convolutions for 24 hourly runs, transparently combined with AERMOD for point and area sources.

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52 AERMOD implementation Interactive scenarios: Annual runs for monitoring station location (single source): Finds the N locations (for possible monitoring stations) with a user defined minimum distance AROUND an emission source with the highest annual average concentration over populated areas. Interactive scenarios: Annual runs for monitoring station location (single source): Finds the N locations (for possible monitoring stations) with a user defined minimum distance AROUND an emission source with the highest annual average concentration over populated areas.

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57 AERMOD implementation Interactive scenarios: Annual runs for single source impact assessment: Computes annual average concentration on an hourly basis around a single source, at user defined or automatically located simulated monitoring stations. Interactive scenarios: Annual runs for single source impact assessment: Computes annual average concentration on an hourly basis around a single source, at user defined or automatically located simulated monitoring stations.

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