Interactive Air Quality Model Demos

One part of the AIR-EIA multimedia information resource are on-line interactive simulation models; they are important components of the toolkit for any study and formal impact assessment of air quality issues and are therefor not only included in the description of methods and tools, but made available for direct on-line, interactive use. An interactive Modeling Primer is provided for a didactic introduction to air quiality modeling in the EIA context. Environmental modeling tools developed and implemented by ESS are based on a generic client-server architecture that combines a powerful model server for high-performance computations required for interactive modeling with the flexibility of an HTML or Java based user interface. The models can be used interactively, with the scenario parameters defined through either HTML FORMS or a Java applet; the user specified parameters are sent to the server, where basic data and the model executable are located. The model is triggered through cgi (Common Gateway Interface), and the results are sent back to the client either as a complete GIF (models results displyed over a background map) plus HTML pages, or as data streams interpreted by the Java applet. In addition, the models can store, on the server, any or all of their outputs in various file formats; these data can then be retrieved by the clients e.g., using an ftp request, which opens the possibility to display and analyse the file with local tools on the client machine. Model demos The initial set of models foreseen for inclusion in the on-line demo set include: single-source Gaussian plume equation multiple source (point, area, line) Gaussian short-term model multiple source (point, area, line) Gaussian long-term model dynamic multi-puff model (with diagnostic 3D wind model) dynamic box model (photochemical) dynamic Eulerian 3D model.

The on-line air-quality modeling tools implemented are based on a generic client-server architecture that combines a powerful model server for high-performance computations required for interactive modeling with the flexibility of an HTML or Java based user interface.

The models use a set of server-side scenarios including, e.g., different background data on the geographical domain (background maps, digital terrain models, long-term weather data, source inventories) including very simple base-line scenarios that user can modify.

In addition, a number of selected key parameters describing emission characteristics and the weather can be modified by the user interactively.

Single-Source evaluation

Steady-state Gaussian models are the most commonly used form of air quality simulation models.

To evaluate a single source (industrial point source with an elevated stack), a number of basic equations area available. the example demonstrates the interdependency of meteorological and stack parameters and shows estimated concentrations downwind from a stack.

Regulatory Models

This is an example of the ISC-3 short- and long-term models with an HTML (Frames and FORM) interface; here the server runs either the short-term or long-term version of the model, and returns the results (the spatially distributed concentration field) already displayed over the background map based on a SPOT satellite image of the city of Vienna. The numerical results can also be downloaded by ftp.

The Dynamic Multi-Puff model

This is an example of a simple dynamic model, still based on a Gaussian approach, using however a 3D terrain correction and a 3D wind field. The multi-puff model simulates a sequence of discrete releases from a dynamic source, which it then traces and integrates over the model area. The result produced is a GIS animation.

The main data requirements of the Gaussian plume models fall into two groups:

• the emission and stack parameters
• the meteorological situation.

Emission and stack parameters

They include:

• emission rate; for particles, specific gravity and a size (distribution) are required
• stack height
• stack diamteer
• flue gas exit velocity
• flue gas temperature.

The latter four parameters are used to estimate, with various formulas, the plume rise or virtual stack height, due to momentum and buoancy of the emissions.

Meteorological data

They include:

• wind direction
• wind speed
• atmospheric stability, usually expressed as (Pasquill) stability classes; these are in turn used to select diffusion coefficients.
• mixing height
• exit temperature.

For model formulations that consider wet scavaging, precipitation data are also required.