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Air quality modelling is used for
determining and visualising the significance and impact of emissions to the atmosphere. They are especially useful to policy-makers whose decisions are often based on emission measurements.
Models are linking the emissions to air pollution concentrations and exposure via meteorological data.
The models can normally only be as reliable as the emission inventories they use.
Impact assessment
There will always be a need for both measurements and models. In some cases, a model is actually better than a measurement. Measurements are usually not representative
for a better area, and their quality is sometimes questionable. A
model can provide estimates of concentrations in areas
where one doesn't have measurements, at least, allows for certain refinements. For health impact assessment including exposure evaluations the use of models of some kind is essential.
Forecasts
Models are also necessary for forecasting and planning purposes. Models are presently being developed to combine meteorological forecast models with air pollution dispersion models to enable air quality forecasts in urban areas of Europe. With larger computers and improved information technologies this may represent some of the future public information services.
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Models
in AirQUIS |
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In the modern multi modular environmental information system
like ENSIS/AirQUIS steps have been taken to establish models for air pollution dispersion to enable environmental impact assessment estimates. Models are essential when the programmes are to be used for planning purposes.
The models need as input data some background information on:
- source characteristics and emission data,
- area characteristics (surface roughness, topography etc.),
- measurement data (measurement type, heights etc.),
- meteorological data (wind, stability, mixing height, temperatures etc.),
- dispersion coefficients (type to be used and parameters),
- dry and wet removal coefficients,
- location of receptor points (distances or grid specifications).
A Eulerian type numerical dispersion model is the
EPISODE model developed by
NILU. It represents the most applied model in AirQUIS today. This is a time-dependent finite difference model normally operating in three vertical levels, combined with a sub grid line source
model for traffic and a puff trajectory model for
industry stations to account for subgrid effects close to individual sources. The wind field used as input to the model may be homogeneous or inhomogeneous for each time step dependent upon the meteorological input data available.
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