• Geographic background data including administrative divisions, land use and land cover, population data, transportation networks, water bodies, orography (DEMs), satellite imagery (LANDSAT, SPOT, IKONOS) and aerial photography, that are managed with the embedded GIS, spanning several levels of nested geographioc domains: LIFE+: model domains provides and example.

• Monitoring time-series data, including the linkage to on-line monitoring stations, and the statistical analysis of these time series data;

• Emission inventories for a range of different source types and pollutants (open list, data driven); source types include major stacks and boilers (grouped into industrial plants), small stacks, area sources, line sources, volume sources, and optional mobile sources such as ships or airplanes. An embedded rule-based expert system simplifies the task of estimating unmeasured emissions; temporal patterns, emission time series, VOC speciation lists, are compiled in a georeferenced object oriented hypermedia data structure.

• A range of air quality simulation models, ranging from simple regulatory steady-state Gaussian models (basic models implemented include the USEPA model AERMOD, Release 09292, in both short-term (1-24 hours) and long-term (seasonal, annual, multi-year) implementations) to dynamic multi-layer and 3D model systems (Eulerian and Lagrangian models) including 3D dynamic nested grid photochemical model CAMx, with the non-hydrostatic 3D nested meteorological prognostic model/preprocessor MM5, and optional external third party models such as CMAQ, CALMET/CALPUFF, etc.

Another optional built-in model is an efficient dynamic 3D CFD code, TIMES, (developed by IMM-RAS, Institute for Mathematical Modelling of the Russian Academy of Sciences , partner in the EUREKA E!3266 WEBAIR project) that uses a 3-D dynamic wind field generated by a built in diagnostic wind model, post-processing MM5 generated wind fields. The model can be used both on a regional scale as well as for near-field simulation of street canyons or accidental releases in the vicinity of building obstacles.

Specific applications of these models include:
• traffic:   the simulation and analysis of traffic-generated emissions and immissions
• heating:   the simulation of emission and immissions from domestic heating and the impacts of district heating schemes.
• Linkage to external models covering areas such as the energy system of traffic, i.e., major sources of air pollution; this includes MARKAL-type energy analysis and optimization, as well as linkages to traffic simulation models like EMME/2 and VISUM/DYNEMO;

• Tools for impact assessment range from models for population exposure to an optional rule-based expert system for screening level environmental impact assessment.

• Decision support tools, ranging from simple impact assessment and post-processing tools to complex multi-criteria optimization models for the design of optimal investment strategies in pollution control equipment. For the design of cost-efficient control strategies, AirWare requires cost functions for alternative emission reduction strategies for each source. The results minimizes a complex spatially distributed and non-linear environmental damage function, subject to monetary (net present value) constraints in investment and operation.

The theoretical background of the two-tiered optimization approach is described, for a example, in of the earlier project, SIMTRAP: MC Decision support tools,

Geographical Data

background maps with administrative boundaries, landuse; satellite data or aerial photography and scanned maps can be used together with vector maps; digital elevation model (DEM) for complex terrain; the system can import data from all common GIS and RS/IP systems;
road network (geometry) graph for traffic emission/immission model; the system can import data from traffic simulation systems like EMME/2 or VISUM/DYNEMO.

Population Data

gridded (usually by hectare) or associated with building block boundaries, required for exposure assessment.

Emission Inventories

point sources (major industries, power plants): location, emission rates, stack height; optional: industry background data, production an energy use data, stack diameter, emission temperature and velocity.
area sources (domestic, air ports, industrial estates): location (gridded or set of polygons, emission rate, height.
line sources (traffic): road segment attributes like traffic density, frequency or direct emission data.
optional volume and mobile sources e.g., for ships or airplanes.

Meteorological Data

time-series of basic meteorological data (half hourly or hourly, covering at least one year or the period of interest for the long-term models): wind direction and speed, air temperature, mixing height, stability class, precipitation. Mixing height and stability class can be estimated, if necessary, using cloud cover and/or solar radiation data;
the system can be linked to on-line monitoring networks.
Please note that at least three well spaced stations are required for the (optional) objective analysis module of the wind field generator.

Air Quality Data

hourly or half hourly observation data from one or more observation stations; station location and regular time series for each parameter. Please note that many (spatial) statistical analysis functions require at least three reasonably distant observation stations;
the system can be linked to on-line monitoring networks.

Economic Data

discrete cost functions (investment and operational costs, social costs where applicable) for a set of alternative emission reduction and control strategies for each emission source to be considered (optional for the optimization model).